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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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A Stepper Motor Design Optimization Using by Wong, Chin Wei

“…There is a need to fill this void in the area of small-motor design, and develop a program using Genetic Algorithms (GAs) as an approach to achieve optimization. …”
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Optimizing Visual Sensor Coverage Overlaps for Multiview Surveillance Systems by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

“…Then, the minimization and the maximization arrangements of the coverage overlapping are formulated as discrete optimization problems. The obtained solutions from the dynamic programming technique are evaluated with respect to local and global greedy search algorithms. …”
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Optimizing Visual Sensor Coverage Overlaps for Multiview Surveillance Systems by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

“…Then, the minimization and the maximization arrangements of the coverage overlapping are formulated as discrete optimization problems. The obtained solutions from the dynamic programming technique are evaluated with respect to local and global greedy search algorithms. …”
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Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game by Chang, Kee Tong

“…Therefore, the main objective of this research is to investigate the performance of single objective and bi-objectives of the hybridised EC as a RTS game controller for reinforcement issue. The proposed EC methods are Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), and Pareto-based Differential Evolution (PDE). …”
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Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

“…This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean (KHM) and Spectral Algorithm and eigenvector centrality measure. …”
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Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

“…In this paper, we proposed profound learning strategy to address three primary assignments developing in the zone of skin lesion picture preparation, i.e., dermoscopic highlight, extraction and detection. A profound algorithm comprising of preprocessing in CIELAB color space and Delaunay triangulation based clustering along with Particle Swarm Optimization (PSO) is proposed for the segmentation. …”
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Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension by Affandy

“…Taking into account from those main issues, this study introduces the new model of integrated algorithm-program visualization (ALPROV) for developing program comprehension tool. …”
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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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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

“…Therefore, the SMA method is redesigned for optimal location and sizing based on the total active power loss of the systems. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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Opposition-based Whale Optimization Algorithm by Alamri, Hammoudeh S., Alsariera, Yazan A., Kamal Z., Zamli

“…The OWOA use the Opposition-based method to enhance Whale Optimization Algorithm (WOA) performance. …”
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A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

“…GA is a widely used optimization algorithm based on the concept of survival of the fittest. …”
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