Search Results - (( evolution optimisation based algorithm ) OR ( using solution matching algorithm ))

Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
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A competitive co-evolutionary approach for the nurse scheduling problem by Mohamad Nazri, Maizatul Farhana, Mohd Yusoh, Zeratul Izzah, Basiron, Halizah, Daud, Azlina

“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
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Artificial neural network and inverse solution method for assisted history matching of a reservoir model by Negash, B.M., Vel, A., Elraies, K.A.

“…In recent years, the use of assisted history matching has become prominent among academia and the industry and has significantly shortened the time required for manual history matching. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Malay cuisine cooking recipe recommendation system using Genetic Algorithm (GA) / Nur Nazihah Ismail by Ismail, Nur Nazihah

“…Lastly, this algorithm obtains convergence result and met the optimal solution.…”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

“…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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Ontology matching: in search of challenges ahead by Farooqui, N.K., Noordin, Mohamad Fauzan, Muhammad, AbdulHafeez

“…This paper elaborates technologies, tools, algorithms and methods used by recent ontology matchers. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…Traditional schema theory does not support Lamatckian learning, i.e, forcing the genetic representation to match the solution found by the learning algorithm. …”
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A proposed model for the selection of workers on crowdsourcing platforms utilizing nested criteria matching by Cucus, Ahmad, Mubarak Ali, Al-Fahim, Zafril Rizal, M. Azmi

“…In this study, we examine the worker selection mechanism as explored in prior research and put forth a novel worker selection model incorporating a profile matching algorithm. The subsequent phase involves enhancing the profile matching algorithm to accommodate nested criteria for matching worker requirements. …”
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Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman by Azman, Muhammad Izzat Azri

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Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

“…This project will study the applicability of the combined algorithm for history matching problem. The study conducted on PCA and RLS method shows high chances of success in applying these methods for history matching problem. …”
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Measuring height of high-voltage transmission poles using unmanned aerial vehicle (UAV) imagery by Qayyum A., Malik A.S., Saad N.M., bin Abdullah M.F., Iqbal M., Rasheed W., Bin Ab Abdullah A.R., Hj Jaafar M.Y.

Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data by Laxmi Lydia E., Sharmili N., Nguyen P.T., Hashim W., Maseleno A.

Measuring height of high-voltage transmission poles using unmanned aerial vehicle (UAV) imagery by Qayyum, A., Malik, A.S., Saad, N.M., bin Abdullah, M.F., Iqbal, M., Rasheed, W., Bin Ab Abdullah, A.R., Hj Jaafar, M.Y.

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Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation by Choong, Shin Siang

“…Approximation algorithm is a sub-class of techniques which is able to provide sub-optimal solution(s) with reasonable computational cost. …”
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TRIZ Approach to FYP Title and Supervisor Matching System by Tan, Jing Ting

“…In this paper, the proposed system follows a stepwise Waterfall methodology and utilizes TRIZ principles during the analysis phase to provide a satisfactory solution. The system incorporates an algorithm that considers students' CGPA, preferences, and titles for matching. …”
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A fuzzy case-based reasoning model for software requirements specifications quality assessment by Mostafa S.A., Gunasekaran S.S., Khaleefah S.H., Mustapha A., Jubair M.A., Hassan M.H.

“…The fuzzy Logic technique works on the selected nearest cases and it utilizes similarity measurement methods to classify the cases into no-match, partial-match and complete-match cases. The features matching results assist the revised step of the CBR to generate a new solution. …”