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Parallel Block Methods for Solving Ordinary Differential Equations
Published 2004“…The new codes were then used for the parallel implementation in solving large systems of first and higher order ODEs. …”
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A hybrid intelligent algorithm for solving the bilevel programming models
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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Optimize class time tabling by using genetic algorithm technique in UTHM
Published 2019“…In existing research, many problems involving scheduling have been solved by using genetic algorithm method. There are many other methods that were also being used such as linear programming, integer linear programming, tabu search, ant colony optimization (ACO) algorithm and goal programming. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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An alternative method to solve combined economic emission dispatch problems using flower pollination algorithm
Published 2016“…Flower Pollination Algorithm (FPA) is a new biologically inspired meta-heuristic optimization technique based the pollination process of flowers. …”
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…This research explored and developed new heuristics based on GA for solving VRPSD. New algorithms, journal papers and computerized system were also developed. …”
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Monograph -
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Thalassaemia detection using CBR Algorithm via mobile device
Published 2011“…This thesis proposes a Case-Based Reasoning model for medical diagnosis,particularly for Thalassaemia diagnosis. CBR Algorithm is an algorithm that can solve a new problem by remembering a previous similar situation and by reusing information and knowledge of that situation in a new situation.CBR is suit for solving the problem in Thalassaemia cases.The model is designed and prototype is developed to test the diagnosis accuracy of the model.T his application is focus on Beta Thalassaemia and Haemoglobin E Trait only.For platform, this application will be using the mobile device such as PDA. …”
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Undergraduates Project Papers -
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Integrated immune-commensal-evolutionary programming for economic dispatch and distributed generation installation / Mohd Helmi Mansor
Published 2020“…Therefore, this study proposes a new hybrid technique termed as Immune-Commensal-Evolutionary Programming (ICEP) to solve ED problems of power system. …”
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Thalassaemia detection using CBR Algorithm via mobile device
Published 2011“…This thesis proposes a Case-Based Reasoning model for medical diagnosis,particularly for Thalassaemia diagnosis. CBR Algorithm is an algorithm that can solve a new problem by remembering a previous similar situation and by reusing information and knowledge of that situation in a new situation.CBR is suit for solving the problem in Thalassaemia cases.The model is designed and prototype is developed to test the diagnosis accuracy of the model.T his application is focus on Beta Thalassaemia and Haemoglobin E Trait only.For platform, this application will be using the mobile device such as PDA. …”
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Undergraduates Project Papers -
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Parallel block methods for solving higher order ordinary differential equations directly
Published 1999“…The accuracy of the parallel block and 1-point methods is comparable particularly when finer step sizes are used. A new parallel algorithm for solving systems of ODEs using variable step size and order is also developed. …”
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Applying case reuse and Rule-Based Reasoning (RBR) in object-oriented application framework documentation: Analysis and design
Published 2023Conference Paper -
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Self-similar network traffic using Random Midpoint Displacement (RMD) algorithm / Jumaliah Saarini
Published 2006“…Poisson arrival processes are not self-similar, regardless of degree of aggregation. The way to solve this problem, we applied the existed method in visual C++ programming with used the Random midpoint Displacement (RMD) algorithm. …”
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Student Project -
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A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch
Published 2016“…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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Article -
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A decomposition/aggregation method for solving electrical power dispatch problems
Published 2023“…A program has been developed to demonstrate the algorithm using the MATLAB programming language. …”
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New fundamental theory in solving the royalty payment problem / Wan Noor Afifah Wan Ahmad and Suliadi Firdaus Sufahani
Published 2021“…Therefore, this study applied a new modified shooting method which is Sufahani-Ahmad-Newton-Golden-Royalty Algorithm. …”
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Conference or Workshop Item -
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An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming
Published 2018“…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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