Results for ' K-Medoid Clustering Algorithm'

960 found
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  1.  23
    Illustration Design Model with Clustering Optimization Genetic Algorithm.Jing Liu, Qixing Chen & Xiaoying Tian - 2021 - Complexity 2021:1-10.
    For the application of the standard genetic algorithm in illustration art design, there are still problems such as low search efficiency and high complexity. This paper proposes an illustration art design model based on operator and clustering optimization genetic algorithm. First, during the operation of the genetic algorithm, the values of the crossover probability and the mutation probability are dynamically adjusted according to the characteristics of the population to improve the search efficiency of the algorithm, (...)
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  2.  25
    Improved FCM Algorithm Based on K-Means and Granular Computing.Zhuang Zhi Yan & Wei Jia Lu - 2015 - Journal of Intelligent Systems 24 (2):215-222.
    The fuzzy clustering algorithm has been widely used in the research area and production and life. However, the conventional fuzzy algorithms have a disadvantage of high computational complexity. This article proposes an improved fuzzy C-means algorithm based on K-means and principle of granularity. This algorithm is aiming at solving the problems of optimal number of clusters and sensitivity to the data initialization in the conventional FCM methods. The initialization stage of the K-medoid cluster, which is (...)
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  3.  17
    What Machine Learning Can Tell Us About the Role of Language Dominance in the Diagnostic Accuracy of German LITMUS Non-word and Sentence Repetition Tasks.Lina Abed Ibrahim & István Fekete - 2019 - Frontiers in Psychology 9.
    This study investigates the performance of 21 monolingual and 56 bilingual children aged 5;6-9;0 on German-LITMUS-sentence-repetition (SRT; Hamann et al., 2013) and nonword-repetition-tasks (NWRT; Grimm et al., 2014), which were constructed according to the LITMUS-principles (Language Impairment Testing in Multilingual Settings; Armon-Lotem et al., 2015). Both tasks incorporate complex structures shown to be cross-linguistically challenging for children with Specific Language Impairment (SLI) and aim at minimizing bias against bilingual children while still being indicative of the presence of language impairment across (...)
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  4.  15
    Selecting the Strategic Port of “the Belt and Road” Based on the Global Network.Zihui Yang, Qingchun Meng & Chanjuan Li - 2021 - Complexity 2021:1-17.
    Under “the Belt and Road” initiative, China promoted cooperation between domestic enterprises and international ports vigorously, which brought back fruitful results, while the rational selection of strategic pivots ports and the optimization of the layout of the port network are important guarantees to a further promotion to the economic development of “the Belt and Road” ports and give full play to the driving and radiation role of strategic pivots ports. On the basis of constructing a network of 155 ports in (...)
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  5.  9
    Early Warning of Financial Risk Based on K-Means Clustering Algorithm.Zhangyao Zhu & Na Liu - 2021 - Complexity 2021:1-12.
    The early warning of financial risk is to identify and analyze existing financial risk factors, determine the possibility and severity of occurring risks, and provide scientific basis for risk prevention and management. The fragility of financial system and the destructiveness of financial crisis make it extremely important to build a good financial risk early-warning mechanism. The main idea of the K-means clustering algorithm is to gradually optimize clustering results and constantly redistribute target dataset to each clustering (...)
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  6.  28
    Enhancement of K-means clustering in big data based on equilibrium optimizer algorithm.Omar Saber Qasim, Zakariya Yahya Algamal & Sarah Ghanim Mahmood Al-Kababchee - 2023 - Journal of Intelligent Systems 32 (1).
    Data mining’s primary clustering method has several uses, including gene analysis. A set of unlabeled data is divided into clusters using data features in a clustering study, which is an unsupervised learning problem. Data in a cluster are more comparable to one another than to those in other groups. However, the number of clusters has a direct impact on how well the K-means algorithm performs. In order to find the best solutions for these real-world optimization issues, it (...)
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  7.  22
    Using Big Data Fuzzy K-Means Clustering and Information Fusion Algorithm in English Teaching Ability Evaluation.Chen Zhen - 2021 - Complexity 2021:1-9.
    Aiming at the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, an English teaching ability evaluation algorithm based on big data fuzzy K-means clustering and information fusion is proposed. Firstly, the author uses the idea of K-means clustering to analyze the collected original error data, such as teacher level, teaching facility investment, and policy relevance level, removes the data that the algorithm considers unreliable, uses the remaining valid data to (...)
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  8.  17
    Application of clustering algorithm in complex landscape farmland synthetic aperture radar image segmentation.Mohammad Shabaz, Korhan Cengiz, Zhenxing Hua, Biao Cong & Zhuoran Chen - 2021 - Journal of Intelligent Systems 30 (1):1014-1025.
    In synthetic aperture radar image segmentation field, regional algorithms have shown great potential for image segmentation. The SAR images have a multiplicity of complex texture, which are difficult to be divided as a whole. Existing algorithm may cause mixed super-pixels with different labels due to speckle noise. This study presents the technique based on organization evolution algorithm to improve ISODATA in pixels. This approach effectively filters out the useless local information and successfully introduces the effective information. To verify (...)
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  9.  26
    Precision Marketing Method of E-Commerce Platform Based on Clustering Algorithm.Bei Zhang, Luquan Wang & Yuanyuan Li - 2021 - Complexity 2021:1-10.
    In user cluster analysis, users with the same or similar behavior characteristics are divided into the same group by iterative update clustering, and the core and larger user groups are detected. In this paper, we present the formulation and data mining of the correlation rules based on the clustering algorithm through the definition and procedure of the algorithm. In addition, based on the idea of the K-mode clustering algorithm, this paper proposes a clustering (...)
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  10.  25
    Clustering Input Signals Based Identification Algorithms for Two-Input Single-Output Models with Autoregressive Moving Average Noises.Khalid Abd El Mageed Hag ElAmin - 2020 - Complexity 2020 (1):2498487.
    This study focused on the identification problems of two-input single-output system with moving average noises based on unsupervised learning methods applied to the input signals. The input signal to the autoregressive moving average model is proposed to be arriving from a source with continuous technical and environmental changes as two separate featured input signals. These two input signals were grouped in a number of clusters using the K-means clustering algorithm. The clustered input signals were supplied to the model (...)
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  11.  19
    An Optimized K-Harmonic Means Algorithm Combined with Modified Particle Swarm Optimization and Cuckoo Search Algorithm.Nacer Farajzadeh & Asgarali Bouyer - 2019 - Journal of Intelligent Systems 29 (1):1-18.
    Among the data clustering algorithms, the k-means (KM) algorithm is one of the most popular clustering techniques because of its simplicity and efficiency. However, KM is sensitive to initial centers and it has a local optima problem. The k-harmonic means (KHM) clustering algorithm solves the initialization problem of the KM algorithm, but it also has a local optima problem. In this paper, we develop a new algorithm for solving this problem based on a (...)
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  12.  23
    An Improved Integrated Clustering Learning Strategy Based on Three-Stage Affinity Propagation Algorithm with Density Peak Optimization Theory.Limin Wang, Wenjing Sun, Xuming Han, Zhiyuan Hao, Ruihong Zhou, Jinglin Yu & Milan Parmar - 2021 - Complexity 2021:1-12.
    To better reflect the precise clustering results of the data samples with different shapes and densities for affinity propagation clustering algorithm, an improved integrated clustering learning strategy based on three-stage affinity propagation algorithm with density peak optimization theory was proposed in this paper. DPKT-AP combined the ideology of integrated clustering with the AP algorithm, by introducing the density peak theory and k-means algorithm to carry on the three-stage clustering process. In the (...)
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  13.  40
    Clustering of Brazilian legal judgments about failures in air transport service: an evaluation of different approaches.Isabela Cristina Sabo, Thiago Raulino Dal Pont, Pablo Ernesto Vigneaux Wilton, Aires José Rover & Jomi Fred Hübner - 2021 - Artificial Intelligence and Law 30 (1):21-57.
    The paper presents different clustering approaches in legal judgments from the Special Civil Court located at the Federal University of Santa Catarina. The subject is Consumer Law, specifically cases in which consumers claim moral and material compensation from airlines for service failures. To identify patterns from the dataset, we apply four types of clustering algorithms: Hierarchical and Lingo, K-means and Affinity Propagation. We evaluate the results based on the following criteria: entropy and purity; algorithm's ability in providing (...)
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  14.  24
    Stroke Subtype Clustering by Multifractal Bayesian Denoising with Fuzzy C Means and K-Means Algorithms.Yeliz Karaca, Carlo Cattani, Majaz Moonis & Şengül Bayrak - 2018 - Complexity 2018:1-15.
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  15.  16
    A Genetic Algorithm Based Clustering Approach with Tabu Operation and K-Means Operation.Yongguo Liu, Hua Yan & Kefei Chen - 2010 - Journal of Intelligent Systems 19 (1):17-46.
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  16.  75
    Clustering the Tagged Web.Christopher D. Manning - unknown
    Automatically clustering web pages into semantic groups promises improved search and browsing on the web. In this paper, we demonstrate how user-generated tags from largescale social bookmarking websites such as del.icio.us can be used as a complementary data source to page text and anchor text for improving automatic clustering of web pages. This paper explores the use of tags in 1) K-means clustering in an extended vector space model that includes tags as well as page text and (...)
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  17.  22
    Adaptive Mixed-Attribute Data Clustering Method Based on Density Peaks.Shihua Liu - 2022 - Complexity 2022:1-13.
    The clustering of mixed-attribute data is a vital and challenging issue. The density peaks clustering algorithm brings us a simple and efficient solution, but it mainly focuses on numerical attribute data clustering and cannot be adaptive. In this paper, we studied the adaptive improvement method of such an algorithm and proposed an adaptive mixed-attribute data clustering method based on density peaks called AMDPC. In this algorithm, we used the unified distance metric of mixed-attribute (...)
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  18.  23
    A hybrid particle swarm optimization with multi-objective clustering for dermatologic diseases diagnosis.R. Nagaraja & Ravinder Reddy Baireddy - 2022 - Journal of Intelligent Systems 31 (1):876-890.
    Effective and personalized treatment relies heavily on skin disease categorization. In the stratification of skin disorders, it is crucial to identify the subtypes of illnesses to provide an efficient therapy. To attain this aim, researchers have focused their attention on cluster algorithms for the stratification of skin disorders in recent decades. But, cluster algorithms have real-world drawbacks, including experimental noises, a large number of dimensions, and a poor ability to comprehend. Cluster algorithms, in particular, determine the quality of clusters using (...)
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  19.  37
    Research on Hybrid Collaborative Filtering Recommendation Algorithm Based on the Time Effect and Sentiment Analysis.Xibin Wang, Zhenyu Dai, Hui Li & Jianfeng Yang - 2021 - Complexity 2021:1-11.
    In this study, we focus on the problem of information expiration when using the traditional collaborative filtering algorithm and propose a new collaborative filtering algorithm by integrating the time factor. This algorithm considers information influence attenuation over time, introduces an information retention period based on the information half-value period, and proposes a time-weighted function, which is applied to the nearest neighbor selection and score prediction to assign different time weights to the scores. In addition, to further improve (...)
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  20.  68
    Analyzing Outcomes of Intrauterine Insemination Treatment by Application of Cluster Analysis or Kohonen Neural Networks.Anna Justyna Milewska, Dorota Jankowska, Urszula Cwalina, Teresa Więsak, Dorota Citko, Allen Morgan & Robert Milewski - 2013 - Studies in Logic, Grammar and Rhetoric 35 (1):7-25.
    Intrauterine insemination is one of many treatments provided to infertility patients. Many factors such as, but not limited to, quality of semen, the age of a woman, and reproductive hormone levels contribute to infertility. Therefore, the aim of our study is to establish a statistical probability concerning the prediction of which groups of patients have a very good or poor prognosis for pregnancy after IUI insemination. For that purpose, we compare the results of two analyses: Cluster Analysis and Kohonen Neural (...)
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  21.  17
    Method for identifying trolls in online communities.Е. В Измайлова, Д. А Алексеев, В. В Свечникова & А. В Сорокина - 2023 - Philosophical Problems of IT and Cyberspace (PhilITandC) 2:4-17.
    In the article the problem of recognizing users of social networks, chats and other virtual spaces that are provoked by other users, inciting conflicts between participants of various online communities is investigated. In this work the authors give a brief description of the trolling concept. The relevance of solving the problem of trolling in the social communities of the Internet is shown in connection with the widespread aggressive provocative behavior of individual users in the virtual space, as well as the (...)
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  22.  88
    Performance Modeling of Load Balancing Techniques in Cloud: Some of the Recent Competitive Swarm Artificial Intelligence-based.Jeremy Pitt, B. Sathish Babu & K. Bhargavi - 2020 - Journal of Intelligent Systems 30 (1):40-58.
    Cloud computing deals with voluminous heterogeneous data, and there is a need to effectively distribute the load across clusters of nodes to achieve optimal performance in terms of resource usage, throughput, response time, reliability, fault tolerance, and so on. The swarm intelligence methodologies use artificial intelligence to solve computationally challenging problems like load balancing, scheduling, and resource allocation at finite time intervals. In literature, sufficient works are being carried out to address load balancing problem in the cloud using traditional swarm (...)
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  23.  20
    The Influence of Knowledge Base on the Dual-Innovation Performance of Firms.Liping Zhang, Hailin Li, Chunpei Lin & Xiaoji Wan - 2022 - Frontiers in Psychology 13.
    Dual innovation, which includes exploratory innovation and exploitative innovation, is crucial for firms to obtain a sustainable competitive advantage. The knowledge base of firms greatly influences or even determines the scope, direction, and path of their dual-innovation activities, which drive their innovation process and produce different innovation performances. This study uses data source patents obtained by 285 focal firms in the Chinese new-energy vehicle industry in the period 2015–2020. Five knowledge-base features are selected by analyzing the correlation and multicollinearity, and (...)
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  24.  99
    A Neutrosophic Approach to Study Agnotology: A Case Study on Climate Change Beliefs.Maikel Leyva & Florentin Smarandache - 2024 - Hypersoft Set Methods in Engineering 2 (1).
    Misinformation and biased information significantly impact public perception and political decisions, especially on critical issues such as climate change and environmental conservation. This study aims to understand how indeterminacy and contradiction influence public perception and policy formulation by applying neutrosophic theory to model the complexity and multi-dimensionality of ignorance. Using neutrosophic Likert scales, we capture a nuanced spectrum of opinions on the scientific certainty of human impact on climate change. The results are analyzed through a k-means clustering algorithm (...)
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  25.  27
    Image Recognition Technology in Texture Identification of Marine Sediment Sonar Image.Chao Sun, Li Wang, Nan Wang & Shaohua Jin - 2021 - Complexity 2021:1-8.
    Through the recognition of ocean sediment sonar images, the texture in the image can be classified, which provides an important basis for the classification of ocean sediment. Aiming at the problems of low efficiency, waste of human resources, and low accuracy in the traditional manual side-scan sonar image discrimination, this paper studies the application of image recognition technology in sonar image substrate texture discrimination, which is popular in many fields. At the same time, considering the scale complexity, diversity, multisources, and (...)
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  26.  14
    Visual Performance of Psychological Factors in Interior Design Under the Background of Artificial Intelligence.Yunkai Xu & TianTian Yu - 2022 - Frontiers in Psychology 13.
    Sensation is the reflection of the brain on the individual attributes of objective things that directly act on the sense organs. Feeling is the most elementary cognitive process and the simplest psychological phenomenon. Vision is a kind of sense, and sense is produced by objective things acting on the sense organs. But at present, it is rare to analyze interior design exhibition from the perspective of visual psychology, an emerging science, as an interdisciplinary attempt, only in interior design research. Therefore, (...)
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  27.  11
    Optimization of shared bike paths considering faulty vehicle recovery during dispatch.Donghao Shi - 2022 - Journal of Intelligent Systems 31 (1):1024-1036.
    With the rapid development of China’s social economy and the improvement of the level of urbanization, urban transportation has also been greatly developed. With the booming development of the internet and the sharing economy industry, shared bicycles have emerged as the times requirement. Shared bicycles are a new type of urban transportation without piles. As a green way of travel, shared bicycles have the advantages of convenience, fashion, green, and environmental protection. However, many problems have also arisen in the use (...)
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  28.  18
    A 4D Trajectory Prediction Model Based on the BP Neural Network.Lan Ma, Shan Tian & Zhi-Jun Wu - 2019 - Journal of Intelligent Systems 29 (1):1545-1557.
    To solve the problem that traditional trajectory prediction methods cannot meet the requirements of high-precision, multi-dimensional and real-time prediction, a 4D trajectory prediction model based on the backpropagation (BP) neural network was studied. First, the hierarchical clustering algorithm and the k-means clustering algorithm were adopted to analyze the total flight time. Then, cubic spline interpolation was used to interpolate the flight position to extract the main trajectory feature. The 4D trajectory prediction model was based on the (...)
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  29.  3
    Exploratory techniques to analyse Ecuador's tourism industry.Anita Herrera, Ángel Arroyo, Alfredo Jiménez & Álvaro Herrero - 2024 - Logic Journal of the IGPL 32 (6):1018-1035.
    The analysis of the operation of tourism companies will provide valid information for the design of policies to reactivate the tourism industry, which has been strongly affected during the pandemic generated by COVID-19. The objective of this paper is to use soft computing techniques to analyse tourism companies in Ecuador. First of all, dimensionality reduction methods are applied: principal component analysis, isometric feature mapping and locally linear embedding, on data of tourism enterprises in Ecuador for the year 2015. In addition, (...)
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  30.  27
    Neutrosophic Clustering Algorithm Based on Sparse Regular Term Constraint.Dan Zhang, Yingcang Ma, Hu Zhao & Xiaofei Yang - 2021 - Complexity 2021:1-12.
    Clustering algorithm is one of the important research topics in the field of machine learning. Neutrosophic clustering is the generalization of fuzzy clustering and has been applied to many fields. This paper presents a new neutrosophic clustering algorithm with the help of regularization. Firstly, the regularization term is introduced into the FC-PFS algorithm to generate sparsity, which can reduce the complexity of the algorithm on large data sets. Secondly, we propose a method (...)
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  31.  8
    An FCM clustering algorithm based on the identification of accounting statement whitewashing behavior in universities.Qihao Yang - 2022 - Journal of Intelligent Systems 31 (1):345-355.
    The traditional recognition method of whitewash behavior of accounting statements needs to analyze a large number of special data samples. The learning rate of the algorithm is low, resulting in low recognition accuracy. To solve the aforementioned problems, this article proposes a method to identify the whitewash behavior of university accounting statements based on the FCM clustering algorithm. This article analyzes the motivation of university accounting statement whitewashing behavior, studies the common means of statement whitewashing, and establishes (...)
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  32.  34
    Clustering Algorithms in Hybrid Recommender System on MovieLens Data.Urszula Kuzelewska - 2014 - Studies in Logic, Grammar and Rhetoric 37 (1):125-139.
    Decisions are taken by humans very often during professional as well as leisure activities. It is particularly evident during surfing the Internet: selecting web sites to explore, choosing needed information in search engine results or deciding which product to buy in an on-line store. Recommender systems are electronic applications, the aim of which is to support humans in this decision making process. They are widely used in many applications: adaptive WWW servers, e-learning, music and video preferences, internet stores etc. In (...)
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  33.  22
    Spectral Clustering Algorithm for Cognitive Diagnostic Assessment.Lei Guo, Jing Yang & Naiqing Song - 2020 - Frontiers in Psychology 11.
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  34.  19
    Cloud Security: LKM and Optimal Fuzzy System for Intrusion Detection in Cloud Environment.S. S. Sujatha & S. Immaculate Shyla - 2019 - Journal of Intelligent Systems 29 (1):1626-1642.
    In cloud security, intrusion detection system (IDS) is one of the challenging research areas. In a cloud environment, security incidents such as denial of service, scanning, malware code injection, virus, worm, and password cracking are getting usual. These attacks surely affect the company and may develop a financial loss if not distinguished in time. Therefore, securing the cloud from these types of attack is very much needed. To discover the problem, this paper suggests a novel IDS established on a combination (...)
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  35.  22
    Stable Sparse Classifiers predict cognitive impairment from gait patterns.Tania Aznielle-Rodríguez, Marlis Ontivero-Ortega, Lídice Galán-García, Hichem Sahli & Mitchell Valdés-Sosa - 2022 - Frontiers in Psychology 13.
    BackgroundAlthough gait patterns disturbances are known to be related to cognitive decline, there is no consensus on the possibility of predicting one from the other. It is necessary to find the optimal gait features, experimental protocols, and computational algorithms to achieve this purpose.PurposesTo assess the efficacy of the Stable Sparse Classifiers procedure for discriminating young and healthy older adults, as well as healthy and cognitively impaired elderly groups from their gait patterns. To identify the walking tasks or combinations of tasks (...)
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  36.  18
    Intelligence system of artificial vision for unmanned aerial vehicle.Shkuropat O. A., Shelehov I. V. & Myronenko M. A. - 2020 - Artificial Intelligence Scientific Journal 25 (4):53-58.
    The article considers the method of factor cluster analysis which allows automatically retrain the onboard recognition system of an unmanned aerial system. The task of informational synthesis of an on-board system for identifying frames is solved within the information-extreme intellectual technology of data analysis, based on maxi- mizing the informational ability of the system during machine learning. Based on the functional approach to modeling cognitive processes inherent to humans during forming and making classification decisions, it was proposed a categorical model (...)
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  37.  32
    Development and Supervision of Robo-Advisors under Digital Financial Inclusion in Complex Systems.Wensheng Dai - 2021 - Complexity 2021:1-12.
    With the rapid development of the market economy, there are more and more projects in the financial industry, and their complexity and technical requirements are getting higher and higher. The development of computer technology has promoted the birth of robot consultants, and it is of great significance to use robot consultants to manage and supervise financial industry projects. In order to further analyze the development and supervision of robo-advisors under the digital inclusive financial system, this paper uses complex systems and (...)
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  38.  17
    An Exploration of Factors Linked to Academic Performance in PISA 2018 Through Data Mining Techniques.Adriana Gamazo & Fernando Martínez-Abad - 2020 - Frontiers in Psychology 11:575167.
    International large-scale assessments, such as PISA, provide structured and static data. However, due to its extensive databases, several researchers place it as a reference in Big Data in Education. With the goal of exploring which factors at country, school and student level have a higher relevance in predicting student performance, this paper proposes an Educational Data Mining approach to detect and analyze factors linked to academic performance. To this end, we conducted a secondary data analysis and built decision trees (C4.5 (...)
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  39.  24
    PPI-GA: A Novel Clustering Algorithm to Identify Protein Complexes within Protein-Protein Interaction Networks Using Genetic Algorithm.Naeem Shirmohammady, Habib Izadkhah & Ayaz Isazadeh - 2021 - Complexity 2021:1-14.
    Comprehensive analysis of proteins to evaluate their genetic diversity, study their differences, and respond to the tensions is the main subject of an interdisciplinary field of study called proteomics. The main objective of the proteomics is to detect and quantify proteins and study their post-translational modifications and interactions using protein chemistry, bioinformatics, and biology. Any disturbance in proteins interactive network can act as a source for biological disorders and various diseases such as Alzheimer and cancer. Most current computational methods for (...)
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  40.  16
    Audit Analysis of Abnormal Behavior of Social Security Fund Based on Adaptive Spectral Clustering Algorithm.Yan Wu, Yonghong Chen & Wenhao Ling - 2021 - Complexity 2021:1-11.
    Abnormal behavior detection of social security funds is a method to analyze large-scale data and find abnormal behavior. Although many methods based on spectral clustering have achieved many good results in the practical application of clustering, the research on the spectral clustering algorithm is still in the early stage of development. Many existing algorithms are very sensitive to clustering parameters, especially scale parameters, and need to manually input the number of clustering. Therefore, a density-sensitive (...)
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  41.  15
    k-Means clustering of asymmetric data.Dominik Olszewski - 2012 - In Emilio Corchado, Vaclav Snasel, Ajith Abraham, Michał Woźniak, Manuel Grana & Sung-Bae Cho, Hybrid Artificial Intelligent Systems. Springer. pp. 243--254.
  42.  18
    Design of digital economy consumer psychology prediction model based on canopy clustering algorithm.Yue Zhang, Peng Ruan & Jingfeng Zhao - 2022 - Frontiers in Psychology 13.
    With the continuous improvement of the level of science and technology, the popularization of the Internet and the development of applications, online consumption has become a major force in personal consumption. As a result, digital consumption is born, and digital consumption is not only reflected in transaction consumption at the monetary level. Like some intangible services similar to the use of dating software, it can also become digital consumption. In this environment, a new economic concept, the digital economy, has emerged (...)
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  43.  42
    A Novel Hierarchical Clustering Algorithm Based on Density Peaks for Complex Datasets.Rong Zhou, Yong Zhang, Shengzhong Feng & Nurbol Luktarhan - 2018 - Complexity 2018:1-8.
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  44. An unsupervised clustering algorithm for intrusion detection.G. Yu, A. G. Ali & B. Nabil - forthcoming - Proc. Of the 16th Conference of the Canadian Society for Computational Studies of Intelligence (Ai 2003), Halifax, Nova Scotia, Canada.
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  45.  59
    Polarisation assessment in an intelligent argumentation system using fuzzy clustering algorithm for collaborative decision support.Ravi Santosh Arvapally & Xiaoqing Liu - 2013 - Argument and Computation 4 (3):181-208.
    We developed an on-line intelligent argumentation system which facilitates stakeholders in exchanging dialogues. It provides decision support by capturing stakeholders’ rationale through arguments. As part of the argumentation process, stakeholders tend to both polarise their opinions and form polarisation groups. The challenging issue of assessing argumentation polarisation had not been addressed in argumentation systems until recently. Arvapally, Liu, and Jiang [, ‘Identification of Faction Groups and Leaders in Web-Based Intelligent Argumentation System for Collaborative Decision Support’, in Proceedings of International Conference (...)
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  46.  25
    Interactive Multimodal Television Media Adaptive Visual Communication Based on Clustering Algorithm.Huayuan Yang & Xin Zhang - 2020 - Complexity 2020:1-9.
    This article starts with the environmental changes in human cognition, analyzes the virtual as the main feature of visual perception under digital technology, and explores the transition from passive to active human cognitive activities. With the diversified understanding of visual information, human contradiction of memory also began to become prominent. Aiming at the problem that the existing multimodal TV media recognition methods have low recognition rate of unknown application layer protocols, an adaptive clustering method for identifying unknown application layer (...)
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  47.  56
    Construction of Student Information Management System Based on Data Mining and Clustering Algorithm.XueHong Yin - 2021 - Complexity 2021:1-11.
    Data mining is a new technology developed in recent years. Through data mining, people can discover the valuable and potential knowledge hidden behind the data and provide strong support for scientifically making various business decisions. This paper applies data mining technology to the college student information management system, mines student evaluation information data, uses data mining technology to design student evaluation information modules, and digs out the factors that affect student development and the various relationships between these factors. Predictive assessment (...)
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  48.  11
    Behavior feature extraction method of college students’ social network in sports field based on clustering algorithm.Haiou Sun & Yonggang Wang - 2022 - Journal of Intelligent Systems 31 (1):477-488.
    In order to improve the integrity of the social network behavior feature extraction results for sports college students, this study proposes to be based on the clustering algorithm. This study analyzes the social network information dissemination mechanism in the field of college students’ sports, obtains the real-time social behavior data in the network environment combined with the analysis results, and processes the obtained social network behavior data from two aspects of data cleaning and de-duplication. Using clustering (...) to determine the type of social network user behavior, setting the characteristics of social network behavior attributes, and finally through quantitative and standardized processing, get the results of college students’ sports field social network behavior characteristics extraction. The experimental results showed that the completeness of the method feature extraction results improved to 9.93%, and the average extraction time cost was 0.344 s, with high result integrity and obvious advantages in the extraction speed. (shrink)
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  49.  24
    Interpreting and extending classical agglomerative clustering algorithms using a model-based approach.Dan Klein & Christopher D. Manning - unknown
    erative clustering. First, we show formally that the common heuristic agglomerative clustering algorithms – Ward’s method, single-link, complete-link, and a variant of group-average – are each equivalent to a hierarchical model-based method. This interpretation gives a theoretical explanation of the empirical behavior of these algorithms, as well as a principled approach to resolving practical issues, such as number of clusters or the choice of method. Second, we show how a model-based viewpoint can suggest variations on these basic agglomerative (...)
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  50.  17
    Results of testing, research and analysis of the basic clustering algorithms of numerical data sets.Trokhymchuk R. M. - 2019 - Artificial Intelligence Scientific Journal 24 (1-2):101-107.
    This work is devoted to the testing, research and comparative analysis of the most well-known and widely used methods and algorithms for clustering numerical data sets. Multidimensional scaling was applied to evaluate the results of solving the clustering problem by visualizing datasets at all stages of the implementation of the studied algorithms. All algorithms were tested for artificial and real data sets. As a result, for each of the investigated algorithms, the main characteristics were formulated in the form (...)
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