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83 articles for “Hybrid Algorithms”
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Research ArticleOpen accessIn the abstractGeometrical Approach to a New Hybrid Grid-Based Gravitational Clustering AlgorithmFaisal Bin Al Abid, A.N.M. Rezaul Karim, Golam Rahman ChowdhuryIn the past years, several clustering algorithms have been developed, for example, K-means, K-medoid. Most of these algorithms have the common problem of selecting the appropriate number of clusters and these algorithms are sensitive to noisy data and would cause less accurate clustering of the data set. Therefore, this paper introduces a new Hybrid Grid-based Gravitational Clustering Algorithm (HGGCA) geometrically, … …Journal of Computer Science, Vol. 17, Issue 3 · 9 Mar 2021 · 6,783 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural NetworkMohamed Grida, Lamiaa Fayed, Mohamed HassanRecommender systems are powerful systems that give added value to business and corporation. They are relatively recent technology and they will only keep improving in the future. The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system. The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy. The hybrid … …Journal of Computer Science, Vol. 16, Issue 12 · 13 Jan 2021 · 6,731 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Survey of Methods for Managing the Classification and Solution of Data Imbalance ProblemKhan Md. Hasib, Md. Sadiq Iqbal, Faisal Muhammad Shah et al.The problem of class imbalance is extensive for focusing on numerous applications in the real world. In such a situation, nearly all of the examples are labeled as one class called majority class, while far fewer examples are labeled as the other class usually, the more important class is called minority. Over the last few years, several types of research … …Journal of Computer Science, Vol. 16, Issue 11 · 13 Nov 2020 · 10,120 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Ant Colony Optimization and Genetic Algorithm for Rule InductionHayder Naser Khraibet AL-Behadili, Ku Ruhana Ku-Mahamud, Rafid SagbanIn this study, a hybrid rule-based classifier namely, ant colony optimization/genetic algorithm ACO/GA is introduced to improve the classification accuracy of Ant-Miner classifier by using GA. The Ant-Miner classifier is efficient, useful and commonly used for solving rule-based classification problems in data mining. Ant-Miner, which is an ACO variant, suffers from local optimization problem which affects its performance. In our … …Journal of Computer Science, Vol. 16, Issue 7 · 24 Jul 2020 · 7,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiagnosis of Hepatitis Disease with Logistic Regression and Artificial Neural NetworksAlaa M. Elsayad, Ahmed M. Nassef, Mujahed Al-DhaifallahHepatitis C refers to the inflammatory state of the liver caused by viruses, bacteria, fungi, and exposure to toxins such as alcohol and self-immunity. The diagnosis requires investigating many laboratory tests and comparing the results to those of the former patients with the same conditions. This study presents the results of our experiments to build a hybrid system that combines … …Journal of Computer Science, Vol. 16, Issue 3 · 27 Mar 2020 · 7,466 accessesView PDFCite
Research ArticleOpen accessIn the abstractSolving Multi-Objective Master Production Scheduling Model of Kalak Refinery System Using Hybrid Evolutionary Imperialist Competitive AlgorithmShereen Saleem Sadiq, Adnan Mohsin Abdulazeez, Habibollah HaronThe improvement of operational planning in the field of oil refinery management is becoming increasingly essential and valid. The influential primary factor, among others, is the ever-changing economic climate. The industry must continually assess the potential impacts of variations in the final product demand, price fluctuations, crude oil compositions and even seek out immediate opportunities within the market. The Master … …Journal of Computer Science, Vol. 16, Issue 2 · 12 Feb 2020 · 7,827 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Risk Management Strategies for Additive Manufacturing Supply ChainsBandar Altubaishe, Jahlani Clarke, Christina McWilliams, Salil DesaiSupplier selection is an important strategic decision to be made in additive manufacturing supply chains. This paper presents a hybrid Analytic Hierarchy Process-Preference Ranking Organization Method for Enrichment of Evaluations (AHP-PROMETHEE) algorithms-based Failure Mode and Effects Analysis (FMEA) for supplier selection in a risk-based environment. Our approach is contrasted with an FMEA based on a Fuzzy Analytic Hierarchy Process (FAHP) … …American Journal of Applied Sciences, Vol. 16, Issue 8 · 17 Oct 2019 · 8,581 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficiency of Hybrid MPPT Techniques Based on ANN and PSO for Photovoltaic Systems under Partially Shading ConditionsMax Tatsuhiko Mitsuya, Anderson Alvarenga de Moura MenesesHybrid Maximum Power Point Tracking (MPPT) algorithms have been investigated as an alternative to improve the performance of conventional MPPT, such as Perturb and Observe (P&O), Incremental Conductance (InC) and Hill Climbing (HC) in Photovoltaic (PV) systems under Partially Shading Co+ndition (PSC). In the present article, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) hybridized with P&O algorithm for … …American Journal of Engineering and Applied Sciences, Vol. 12, Issue 4 · 3 Oct 2019 · 8,888 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Wide Scale Classification of Class Imbalance Problem and its Solutions: A Systematic Literature ReviewGillala Rekha, Amit Kumar Tyagi, V. Krishna ReddyIn today’s world, most of the data (real world) is present in imbalanced form by nature. This is because of not having efficient algorithms to put this data (i.e., generated data by billion of internet- connected devices (IoTs)) in respective format. Imbalanced data poses a great challenge to (both) data mining and machine learning algorithms. The imbalanced dataset consists of … …Journal of Computer Science, Vol. 15, Issue 7 · 3 Jul 2019 · 9,372 accessesView PDFCite
Research ArticleOpen accessIn the abstractMCMC-Fuzzy: A Fuzzy Metric Applied to Bayesian Network Structure LearningBeatriz Wilges, Ademar Crotti Junior, Silvia Modesto NassarBayesian network structure learning is considered a complex task as the number of possible structures grows exponentially with the number of variables. Two main methods are used for Bayesian network structure learning: Conditional independence, a method in which a structure is created consistently with independence tests performed on data; and the heuristic search method that explores the structure space. Hybrid … …Journal of Computer Science, Vol. 14, Issue 8 · 24 Aug 2018 · 8,243 accessesView PDFCite