Search Results - parallel (attributed OR contributions) ((classification algorithm) OR (optimization algorithm))

Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…The average classification accuracies for the proposed ACOMV–SVM and IACOMV-SVM algorithms are 97.28 and 97.91 respectively. …”
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A GPGPU Approach to Accelerate Ant Swarm Optimization Rough Reducts (ASORR) Algorithm by Udayanti, Erika Devi, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Nugroho, Fajar Agung

“…In order to find a reducts, a such applications of rough set uses a discernibility matrix. Ant Swarm Optimization Rough Reducts (ASORR) algorithm is used in rough reducts calculation for identifying significant attribute set optimally. …”
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Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network by Sefidgar, Seyed Mohammad Hossein

“…This method resulted around 99% of classification rate. To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour by Hadi , Naghavipour

“…On that basis, the second contribution of this thesis is proposing a fast fuzzy evolutionary algorithm with minimal stochastic behaviour. …”
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Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm by Khoo, Thau Soon

“…Our algorithm uses non-fitness evolutionary distributed parallelized adaptive large neighbourhood search (NEDPALNS). …”
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Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization by Hazmi Wahab, Muhammad Hafizul

“…The central challenge in Automatic Text Summarization (ATS) is efficiently generating machine-generated text summaries through optimization algorithms, a critical component for systems dealing with textual information processing. …”
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ROA-CONS: raccoon optimization job scheduling by Koohi, Sina Zangbari, Abdul Hamid, Nor Asilah Wati, Othman, Mohamed, Ibragimov, Gafurjan

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Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm by Mohd Abdul Hadi, Osman, Mohd Fadzil Faisae, Ab Rashid, Nik Mohd Zuki, Nik Mohamed, Muhammad Ammar, Nik Mu’tasim

“…Through an extensive computational experiment involving a well-known benchmark suite, the ABC algorithm demonstrated remarkable performance, consistently outperforming several popular metaheuristic algorithms, including Genetic Algorithms, Particle Swarm Optimization, Memetic Algorithms, and Whale Optimization Algorithm in 75% of the problems. …”
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Hybrid harmony search-artificial intelligence models in credit scoring by Goh, Rui Ying

“…Then, the two types of features importance computed from RF algorithm are utilized for the attributes explanation. …”
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Optimizing photovoltaic arrays : A tested dataset of newly manufactured PV modules for data-driven analysis and algorithm development by Al Mansur, Ahmed, Islam, Md Imamul, Alam, Md Sabbir, Mohd Shawal, Jadin, Sultana, Zinat, Ali, Md Mortuza Naushad, Shihavuddin, Asm S.M.

“…The dataset serves as a valuable resource for academic research, particularly in the domain of PV array optimization. To facilitate optimization efforts, different algorithms have been explored in the literature. …”
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A Dual Recurrent Neural Network-based Hybrid Approach for Solving Convex Quadratic Bi-Level Programming Problem by WATADA, J., ROY, A., LI, J., WANG, B., WANG, S.

“…Hence, we believe the proposed algorithm will contribute to solving quadratic-BLPPs involved in various engineering, management, and finance applications. …”
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Adaptive genetic algorithm to improve negotiation process by agents e-commerce by Ebadi, Sahar

“…Second contribution is made by applying an improved genetic algorithm in offer generation mechanism and producing high quality, mutually acceptable offers. …”
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi by Hosseiny Fatemi, Mohammad Reza

“…This thesis is concerned with algorithm optimization and efficient low cost architecture design for integer motion estimation (IME) and sub-pixel motion estimation (SME) of H.264/AVC. …”
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Hybrid intelligent methods for parameter identification and load frequency control in power system by Aqeel Sakhy, Jaber

“…A new method from the improvement of Particle Swarm Optimization (PSO) is developed in order to find the best global optimal value. …”
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