Search Results - (( developing case genetic algorithm ) OR ( java code classification algorithm ))

Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

“…A formal algorithm that can be applied to any two related Java-based source codes examples is invented to generate the semantics of these source codes. …”
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Solving transcendental equation using genetic algorithm / Masitah Hambari by Masitah , Hambari

“…This project studies the potential of using Genetic Algorithm and develops a program in order to solve Transcendental Equation in optimizing problem domain. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

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A genetic algorithm for the cryptanalysis of Chor-Rivest knapsack public key cryptosystem (PKC) by Taha, Imad, Sahasrabuddhe, H.V.

“…In this paper we develop a genetic algorithm as a method for cryptanalysing the Chor- Rivest knapsack PKC. …”
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Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

“…The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. …”
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Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

“…Build up a user interface by using Visual Studio Code (VSC) to run the coding of Cascading Style Sheet (CSS), Hyper Text Markup Language (HTML) and JavaScript (JS) as a webpage and connect to Azure Machine Learning Model and this will allow the user from using the model from a webpage when they have active internet with any devices.…”
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Reverse logistics network optimizing by genetic algorithm: a case study of automotive wiring harnesses by Sadrnia, Abdolhossein, Ismail, Napsiah, Mohd Ariffin, Mohd Khairol Anuar, Zulkifli, Norzima, Boyer, Omid

“…Thus, an evolutionary algorithm based genetic algorithm (GA) is applied as a solution methodology to solve mixed integer linear programming model and find the optimum solution. …”
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Applying case reuse and Rule-Based Reasoning (RBR) in object-oriented application framework documentation: Analysis and design by Jani H.M., Lee S.P.

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Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

“…The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. …”
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Optimisation of multi-stage production-inspection stations using genetic algorithm by Hassan, Azmi, Pham, Duc Trung

“…The optimisation tool to be considered is Genetic Algorithm (GA). An introduction to the concepts of the GA and its encoding of the solutions to the problems in a genetic form and the evaluation of the resulting genetic code to give the fitness of those solutions will be discussed. …”
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Multi-population Genetic Algorithm for Rich Vehicle Routing Problems by Agany Manyiel, Joseph Mabor

“…Results from the experiments show that MPGA-RVRP performs better compared to benchmark, Multi-objective Genetic Algorithm (MOGA). A web-based logistic sys�tem has also been developed as use case for MPGA-RVRP.…”
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Rational drug design using genetic algorithm: case of malaria disease by Al-Safi, Hassen Mohammed, Alshaikhli, Imad Fakhri Taha

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Study of optimal EG placement in radial distribution system using real coded genetic algorithm by M. H., Sulaiman, Omar, Aliman

“…This paper proposes a study of embedded generation (EG) placement in radial distribution system by utilizing real coded genetic algorithm (RCGA) technique. Several cases of EG models placements are studied in order to minimize the total power losses and to improve voltage profiles of the system. …”
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Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems by Homayouni, Seyed Mahdi

“…This is addressed as genetic fuzzy logic controller (GFLC). The GFLC methodology is used to develop two production control architectures named “genetic distributed fuzzy” (GDF), and “genetic supervisory fuzzy” (GSF) controllers. …”
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Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

“…HOGA, as a new effective tool for multi-objective optimization by evolutionary algorithm is used in this research. HOGA (Hybrid Optimization by Genetic Algorithms) is developed by Dr.Lopez from Zaragoza university in Spain. …”
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Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm by Nukman, Y., Hassan, M.A., Harizam, M.Z.

“…To overcome such problem, a hybrid genetic algorithm-based Taguchi ANN (GA-Taguchi ANN) has been developed. …”
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Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

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Penggunaan kaedah algoritma genetik dalam permasalahan penjadualan PCB: kajian kes di industri elektronik by Zalinda Othman

“…Genetic algorithm formulation included chromosome representations and genetic operators have been developed to suit the scheduling problems that take into account the alternative production lines. …”
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Faculty timetabling using genetic algorithm by Liong, Boon Yaun

“…Faculty Timetabling using Genetic Algorithm (FTGA) is an application that generate optimum timetable for faculty.The target user of this application is faculty staff who responsible in generate timetable.The problem statement of the project is many clashing exist in the timetable.Faculty staff needs to solve the clashing manually.This will waste time and it is a problem for staff to solve the clashing.By implement GA,clashing will be reduced.The objective of the project is to develop aprototype in scheduling application for generates an optimum timetable for a faculty.Genetic algorithm will be implemented.The scope of FTGA is Faculty of Computer Systems & Software Engineering (FCSSE).The methodology use in this project is prototype model.The testing result show 95 out of 100 test cases achieved the maximum fitness value which means there is no clashing in the timetable.The maximum generation is set to 15 generation.Population for each generation is 3 populations.Percentage of FTGA solve the problem is 95%.…”
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Multi-criteria evolutionary regression test prioritization for dynamic object-oriented programs by Bello, Abdulkarim, Md. Sultan, Abubakar, Shehu, Sirajo

“…This paper proposed new regression testing technique that uses multiple coverage criteria for regression test prioritization of dynamic object-oriented language using genetic algorithm. Index terms - Regression testing, multi-criteria, test case, test case prioritization, Python, genetic algorithm.…”
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