Search Results - (( developing convex function algorithm ) OR ( java swarm optimization algorithm ))

Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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New Quasi-Newton Equation And Method Via Higher Order Tensor Models by Gholilou, Fahimeh Biglari

“…To approximate the curvature of the objective function, more available information from the function-values and gradient is employed. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

“…Clustering problem is discussed as a problem of non-smooth, non-convex optimization and a new method for solving this optimization problem is developed. …”
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Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail by Ismail, Nor Laili

“…The proposed HEBMO optimisation algorithm was employed to solve the convex and non-convex economic dispatch problems. …”
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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

“…DE has effectively solved various global optimization problems, including benchmark functions. These problems have shown different challenging characteristics such as non-convexity, non-linearity, and/or multi-modality which became difficult for traditional non-linear programming to deal with. …”
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Integrated immune-commensal-evolutionary programming for economic dispatch and distributed generation installation / Mohd Helmi Mansor by Mansor, Mohd Helmi

“…Convex and nonconvex ED problems have been solved using ICEP with two objective functions (total production cost minimization and total system loss minimization). …”
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Optimal reactive power dispatch using multistage artificial immune system by Nordin N.F., Mansor M.H., Kamil K., Roslan N.

“…Another thing to note is that ORPD has a few major targets and objectives which are to reduce the active or real power losses, to improve the voltage profile, to reduce transmission costs, and to increase system stability. Non-convex, non-linear, and multimodal problems make the development of intelligent algorithms to solve the reactive power dispatch problem highly relevant. …”

A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
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Enhanced PAPR reduction and channel estimation techniques in multi-carrier wireless communication system by Ali Kareem, Nahar

“…First, a novel rotating phase shift (RPS) based on signal scrambling to reduce PAPR in OFDM system had been proposed. The search algorithm was used to solve the convex problem in selecting PAPR-RPS best phase shift factor based on the cost of computational complexity. …”
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