Search Results - (( using computing learning algorithm ) OR ( software optimization method algorithm ))
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Training functional link neural network with ant lion optimizer
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Rao-SVM machine learning algorithm for intrusion detection system
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim
Published 2021“…Determination of high performance and lower computing time with simple algorithm is therefore continuously established. …”
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Enhancing Classification Algorithms with Metaheuristic Technique
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Deep reinforcement learning online offloading for SWIPT multiple access edge computing network
Published 2021“…Deep Q network (DQN) is used to learn the binary offloading decisions from the learning experience. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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A fast learning network with improved particle swarm optimization for intrusion detection system
Published 2019“…The Fast Learning Network (FLN) is one of the new machine learning algorithms that are easy to implement, computationally efficient, and with excellent learning performance characteristics. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
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Nature-inspired parameter controllers for ACO-based reactive search
Published 2015“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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