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

Route Optimization System by Zulkifli, Abdul Hayy

“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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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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Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

“…This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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Optimize class time tabling by using genetic algorithm technique in UTHM by Ahmad, Izah Rafidah

“…This research used genetic algorithm (GA) that was applied to java programming languages with a goal of reducing conflict and optimizing the fitness. …”
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Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite by Suali, Anjila J., Nuraminah Ramli, Rozmie Razif Othman, Hasneeza Liza Zakaria, Iszaidy Ismail, Nor Shahida Mohd Jamail, Rimuljo Hendradi, Nurol Husna Che Rose

“…This study proposes a combinatorial testing method utilizing the Whale Optimization Algorithm (WOA). …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…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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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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Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

“…Metaheuristic algorithms have been used successfully for solving different optimization problems. …”
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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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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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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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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…An inappropriate selection of materials for engineering component would result in entire product failure which ultimately has a negative impact on the society. Several algorithms, methods and spreadsheets are being proposed by various researchers in this field to improve materials selection. …”
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Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

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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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