Search Results - (( using function a algorithm ) OR ( using optimization approach algorithm ))

Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network by Ismail Abdullah, Kalid Abdlkader Marsal

Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy by Bhandari, A.K., Singh, V.K, Kumar, A., Singh, G.K.

“…A new approach of CS and WDO algorithm is used for selection of optimal threshold value. …”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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Optimal overcurrent relay solutions for protection coordination using metaheuristics approaches with penalty function method by Noor Zaihah, Jamal, Mohd Herwan, Sulaiman, Abdul, Nasir, Jabbar, Waheb A.

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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm by Krishnan P.S., Paw J.K.S., Kiong T.S.

New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

“…All the methods and data analysis were carried out using MATLAB simulator. Generally, the average results indicates that the newly developed algorithm retrieved better than original MABSA in finding a minimum point which increment 5.833% better than original MABSA, and new algorithm retrieved 5.204% more better than global optimum value. …”
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The optimization of technical trading strategy using genetic algorithm approach / Khairunnisa Musa by Musa, Khairunnisa

“…Genetic algorithm is used as a tool to efficiently search for the most attractive solution as a suggestion for the trader to trade in foreign currencies. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

“…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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A multiobjective simulated Kalman filter optimization algorithm by A. Azwan, A. Razak, Mohd Falfazli, Mat Jusof, Ahmad Nor Kasruddin, Nasir, Mohd Ashraf, Ahmad

“…This paper presents a new multiobjective type optimization algorithm known as a Multiobjective Optimization Simulated Kalman Filter (MOSKF). …”
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A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network by Gumaida, Bassam, Abubakar, Adamu

“…Results: Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other op- timization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). …”
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Hybrid of firefly algorithm and pattern search for solving optimization problems by Wahid, Fazli, Ghazali, Rozaida

“…Firefly algorithm (FA) is a newly introduced meta-heuristic, nature-inspired, stochastic algorithm for solving various types of optimization problems. …”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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Global gbest guided-artificial bee colony algorithm for numerical function optimization by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

“…Numerous computational algorithms are used to obtain a high performance in solving mathematics, engineering and statistical complexities. …”
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Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh by Hisham Ahmad, Theeb Shehadeh

“…The SSO is tested with several benchmark functions used in the area of optimization. The obtained results are compared with the results of four algorithms. …”
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Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems by Mansor, Nur Farraliza

“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach by Ab. Malik, Rosely, Jamil S., Mohamed

“…From standard static formula for bearing capacity of a single pile foundation, an algorithm using a reliability approach for the determination of service load was developed. …”
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Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer by Alam, Mohammad Khurshed

“…The main goal of this study is to use a cuttingedge version of recent metaheuristic algorithm, namely Moth-Flame Optimizer (MFO) algorithm for solving the mentioned OPF problems. …”
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A true annealing approach to the marriage in honey-bees optimization algorithm by Teo, Jason Tze Wi, Hussein A. Abbass

“…The overall performance of the MBO algorithm was found to have improved significantly using the proposed annealing function. …”
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Optimal Power Flow Solution With Stochastic Renewable Energies Using Nature Inspired Algorithm by Abdul Mu’iz Zulfadli, Ab Wahab

“…By the end of this study, this algorithm should have been demonstrated to be a process that is simple to use and capable of searching for a nearglobal optimal solution with significant convergence and effectiveness when compared to other algorithms.…”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct... by Wong Ling Ai

“…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”