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An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…Nature-inspired optimization-based clustering techniques are powerful, robust and more sophisticated than the conventional clustering methods due to their stochastic and heuristic characteristics. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Logic mining method via hybrid discrete hopfield neural network by Guo, Yueling, Mohd Kasihmuddin, Mohd Shareduwan, Zamri, Nur Ezlin, Li, Jia, Romli, Nurul Atiqah, Mansor, Mohd Asyraf, Ruzai, Wan Nur Aqlili

“…The first contribution involves the incorporation of a Hybrid Differential Evolution Algorithm to accelerate the optimization of synaptic weights during the training phase. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…The third method is the hybridization of BPSO and Binary Differential Evolution, namely Binary Particle Swarm Optimization Differential Evolution (BPSODE). …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

“…This study is an attempt to design a method for an autonomous pattern classification and recognition system for emotion recognition. …”
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A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
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Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

“…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. A thorough literature evaluation is required to have a comprehensive overview of the current research on utilizing deep learning methods for email spam classification. …”
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Artificial fish swarm optimization for multilayer network learning in classification problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam

“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN. …”
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Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

“…To attain this essential research purpose, a minimum set of genes that can assure higher performance in classification using data mining algorithms need to be detected. …”
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EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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Optimizing optimal path trace back for Smith-Waterman algorithm using structural modelling technique by Saliman, Nur Farah Ain

“…The optimizing of optimal path trace back system for Smith-Waterman algorithm using structural modelling techniques are presented in this paper. …”
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Optimizing optimal path trace back system for Smith-Waterman algorithm using structural modelling technique: article by Saliman, Nur Farah Ain

“…back system for Smith-Waterman Algorithm using Structural Modelling Technique. The objectives for this paper are to optimize the best trace back scanning performance and also to design the simple architecture in order to reduce the runtime. …”
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Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman by Isman, Muhammad Iskandar

“…Therefore, in this research, will be use Ant Colony Optimization (ACO) algorithm as an optimize technique that provide a shortest path of defining a successor that is their highest value of criteria. …”
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Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

“…In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”