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A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch by Mohamad Ridzuan, Mohamad Radzi, Hassan, Elia Erwani, Abdullah, Abdul Rahim, Bahaman, Nazrulazhar, Abdul Kadir, Aida Fazliana

“…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Evolutionary cost cognizant regression test prioritization for object-oriented programs based on fault dependency by Bello, AbdulKarim, Md Sultan, Abu Bakar, Abdul Ghani, Abdul Azim, Zulzalil, Hazura

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Performance analysis of three ANN models using improved fast evolutionary programming for power output prediction in grid-connected photovoltaic system / Puteri Nor Ashikin Megat Y... by Megat Yunus, Puteri Nor Ashikin, Sulaiman, Shahril Irwan, Omar, Ahmad Maliki

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Automated synthesis of mobile game environments and rulesets using a hybridized interactive evolutionary programming approach by Jia, Hui Ong, Teo, Jason Tze Wi

“…By hybridizing Evolutionary Programming (EP) with Interactive Evolutionary Algorithm (IEA), game rules and its playing environment will be automatically generated for an arcade-type game that can be played on the Android mobile platform. …”
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Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach by Lai, V., Ahmed, Ali Najah, Malek, Marlinda Abdul, El-Shafie, Ahmed, El-Shafie, Amr

“…This study has an important implication for the population in ECPM since the predicted sea level could be used as an early warning signal to help prevent severe erosion and facilitate early evacuation of affected communities in case of flood inundation. Genetic Programming (GP) algorithm is an example of an evolutionary algorithm (EA) in the field of evolutionally computation (EC) and, more broadly, in Artificial Intelligence. …”
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Identification of maximum loadability in power system with line outages using chaotic mutation immune evolutionary programming / Sharifah Azma Syed Mustaffa, Ismail Musirin and Muh... by Syed Mustaff, Sharifah Azma, Musirin, Ismail, Othman, Muhammad Murtadha

“…This paper proposes a new algorithm namely Chaotic Mutation Immune Evolutionary Programming (CMIEP) for maximum loadability under N-1 contingency in a transmission system. …”
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Solving economic load dispatch using immune evolutionary programming (IEP) optimization technique by Raja Muhammad Safarin Raja Kechek

Using genetic algorithms as image watermarking performance optimizer / Zuhaili Zahid by Zahid, Zuhaili

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A hybrid optimization technique for solving economic emission load dispatch problems by Aisyah binti Nordin

Optimal coordination of overcurrent relay protection using evolutionary programming / Noor Shah Rizal Abdul Manap by Noor Shah Rizal, Abdul Manap

“…Therefore, this research employed a metaheuristic optimization for Evolutionary Programming (EP) to find the optimum time for optimization overcurrent protection relay in radial distribution system. …”
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Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game by Chang, Kee Tong

“…The proposed EC methods are Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), and Pareto-based Differential Evolution (PDE). …”
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Invigilation timetabling system using genetic algorithm (GA) / Shahirah Mohamed Hatim by Shahirah, Mohamed Hatim

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Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach by Lai V., Ahmed A.N., Malek M.A., El-Shafie A., El-Shafie A.

“…This study has an important implication for the population in ECPM since the predicted sea level could be used as an early warning signal to help prevent severe erosion and facilitate early evacuation of affected communities in case of flood inundation. Genetic Programming (GP) algorithm is an example of an evolutionary algorithm (EA) in the field of evolutionally computation (EC) and, more broadly, in Artificial Intelligence. …”

Analysis of vehicular traffic flow of main road and alternative road in Kuala Terengganu / Nur Aribah Farzana Arifen & Nur Aiman Salsabila Hashim by Arifen, Nur Aribah Farzana, Hashim, Nur Aiman Salsabila

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An optimal mesh algorithm for remote protein homology detection by M. Abdullah, Firdaus, M. Othman, Razib, Kasim, Shahreen, Hashim, Rathiah, Hassan, Rohayanti, Asmuni, Hishammuddin, Taliba, Jumail

“…This paper also shows that the use of the refinement algorithm increases the performance of the multiple alignments programs by at least 4%.…”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

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Some metaheuristic algorithms for solving multiple cross-functional team selection problems by Ngo, S.T., Jaafar, J., Izzatdin, A.A., Tong, G.T., Bui, A.N.

“…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

“…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. …”
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