Search Results - (( developing future generation algorithm ) OR ( java data optimization algorithm ))

Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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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

“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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A random search based effective algorithm for pairwise test data generation by Sabira, Khatun, K. F., Rabbi, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

“…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

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EasyA: Easy and effective way to generate pairwise test data by Rabbi, Khandakar Fazley, Sabira, Khatun, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

“…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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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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Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

“…After generating the future climate parameters, the predicted stream flow by ANN and estimated future evaporation (convert future minimum and maximum temperature generated by LARS-WG into future evaporation by penman formula) are exported to the constructed models to predict the future power generation output. …”
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Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem by Ismail, Zuhaimy, Nurhadi, Irhamah, Zainuddin, Zaitul Marlizawati

“…New algorithms, journal papers and computerized system were also developed. …”
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Microgrid control methods toward achieving sustainable energy management by Roslan M.F., Hannan M.A., Ker P.J., Uddin M.N.

On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…Genetic Algorithm (GA), Ant Colony (AC), Simulated Annealling (SA), Particle Swarm Optimization, and Harmony Search Algorithm (HS) as their basis in an effort to generate the most optimal solution. …”
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Prediction of UPSR Result using clonal selection algorithm (PUR) / Muhammed Khaleeq Shafii by Shafii, Muhammed Khaleeq

“…This would give a brief overview on which techniques or algorithms give better optimization and faster results in generating Prediction of UPSR result. …”
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil by Jamli, Mohd Radhi Fauzan, Ahmad Fadzil, Ahmad Firdaus

“…Traditional methods of timetable generation lack the adaptability needed to tackle these complexities, necessitating the development of an innovative solution. …”
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Allocation and sizing of distributed generation (DG) using Particle Swarm Optimization (PSO) technique for loss minimization: article / Junainah Pardi by Pardi, Junainah

“…Distributed generator (DG) is playing major role to supply energy resources and also for the development of co-generation plant which is absolutely very important in the electric power systems of the near future. …”
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Allocation and sizing of distributed generation (DG) using Particle Swarm Optimization (PSO) technique for loss minimization / Junainah Pardi by Pardi, Junainah

“…Distributed generator (DG) is playing major role to supply energy resources and also for the development of co-generation plant which is absolutely very important in the electric power systems of the near future. …”
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Ontology matching: in search of challenges ahead by Farooqui, N.K., Noordin, Mohamad Fauzan, Muhammad, AbdulHafeez

“…This paper presents key features and challenges for the development of the next generation ontology matcher. …”
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SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR by FUNG , CHUN TING

“…In the final part of this report, conclusions are drawn and some future work for future development is proposed.…”
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Job shop rescheduling using a hybrid artificial immune system and genetic algorithm model by Mohamed Din, Aniza, Ku-Mahamud, Ku Ruhana, Yusof, Yuhanis, Mahmuddin, Massudi

“…This paper discusses on developing a hybrid model to tackle the problem of changing environment in the job shop scheduling problem.The main idea is to develop building blocks of partial schedules using the model developed that can be used to provide backup solutions when disturbances occur during production.This model hybridizes genetic algorithm (GA) with artificial immune systems (AIS) techniques to generate these partial schedules.Each partial schedule, also known as antibody, is assigned a fitness value for the selection of final population of best partial schedules. …”
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