Search Results - (( swarm optimization method algorithm ) OR ( _ interaction method algorithm ))

Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

“…Hence, optimization algorithms, consisting of exact and heuristic methods, are crucial for a myriad of real-world applications. …”
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Optimization of biochemical systems production using combination of newton method and particle swarm optimization by Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Irfan, Darmawan, Shahreen, Kasim, Mohd Saberi, Mohamad, Ashraf Osman, Ibrahim

“…In the presented paper, an improved method that combines the Newton method with Particle Swarm Optimization (PSO) algorithm to optimize the production of biochemical systems was discussed and presented in detail. …”
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Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

“…The results showed that the proposed PSO algorithm outperformed the other algorithms in terms of the optimal solutions and the convergence.…”
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An experimental study of modified black hole algorithms by Mohammed, Suad Khairi

“…One of the meta-heuristic optimization methods is Black Hole (BH) algorithm, which is inspired by the black hole in cosmology. …”
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Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation by Alazzawi, A.K., Rais, H.M., Basri, S.

“…This is called hybrid artificial bee colony (HABC) strategy, which is based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. …”
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T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm by Rahman, Mostafijur, Sultana, Dalia, Sabira, Khatun, M. F. M., Jusof, Syamimi Mardiah, Shaharum, Nurhafizah, Abu Talip Yusof, Qaiduzzaman, Khandker M., Hasan, Md. Hasibul, Rahman, Md. Mushfiqur, Hossen, Md. Anwar, Begum, Afsana

“…The reason is that the T-way sequence input interaction is NP-Hard problem. In this research, Fish Swarm algorithm is proposed to adapt with T-way sequence input interaction test strategy. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

“…Advancing multi-objective optimization techniques for cancer treatment strategies, the study strategically incorporates Swarm Intelligence (SI) and Evolutionary Algorithms (EA). …”
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Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…The features are reduced using the particle swarm optimization detection technique in video image sequences to reduce the computational complexity. …”
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A fast learning network with improved particle swarm optimization for intrusion detection system by Ali, Mohammed Hasan

“…In these experiments, it was demonstrated that the FLN optimization method achieved 0.9964 which is a higher accuracy than most of the existing paradigms for classifying network intrusion detection data.…”
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Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

“…In this approach, a combination of interacting two levels HS optimization algorithm is presented. …”
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Correlation with the fundamental PSO and PSO modifications to be hybrid swarm optimization by Hasan, Raed A, Najim, Suhel Shahab, Ahmed, Munef Abdullah

“…A correlation with the fundamental Particle Swarm Optimization (PSO) and PSO modifications demonstrates that hybrid swarm optimization outperforms existing strategies. …”
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Analytical and empirical study of particle swarm optimization with a sigmoid decreasing inertia weight by Adriansyah, Andi, H. M. Amin, Shamsudin

“…The particle swarm optimization (PSO) is an algorithm for finding optimal regions of complex search space through interaction of individuals in a population of particles. …”
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A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali by Mohamed Kamali, Mohd Zahurin

“…Solving MRDE, especially nonlinear MRDE is the central issue in optimal control theory. It has been found that by implementing the ACP algorithm, the solution predicted is approximately close or similar to the exact solution. …”
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Taguchi's T-method with nearest integer-based binary bat algorithm for prediction by Marlan Z.M., Jamaludin K.R., Ramlie F., Harudin N.

“…In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi�s T-method. …”

Using Spiral Dynamic Algorithm for Maximizing Power Production of Wind Farm by Mok, Ren Hao, Raja Mohd Taufika, Raja Ismail, Mohd Ashraf, Ahmad

“…Simulation results demonstrate that the SDA based method produces higher total power production compared to the particle swarm optimization (PSO) and game theoretic (GT) based approaches. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

“…s orthogonal array is used as a variable selection approach in optimizing the predictive model. Due to a fixed and restricted predetermined design array, the orthogonal array is unable to give higher-order interactions between variables, resulting in inferior T-method prediction accuracy. …”

Exploring c Environment (S/O: 12826) by Abdul Rahman, Syariza, Ku Mahamud, Ku Ruhana, Ramli, Razamin, Benjamin, Aida Mauziah, Omar, Mohd Faizal

“…The timetabling problem is to be rectified via hybridization of fly and suitable evolutionary algorithms. The Fruit Fly Optimization Algorithm (FOA) is a method that is still limited in optimization and artificial intelligence area. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

“…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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Multi-Objective PSO with Passive Congregation for Load Balancing Problem by Marufuzzaman M., Timu M.A., Sarkar J., Islam A., Rahman L.F., Sidek L.M.

“…Multi-Objective Particle Swarm Optimization (MOPSO) based on crowding distance (CD) is a popular MOEA method used to balance HLA load. …”