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Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data by Mohd Amin, Nor Azrita, Adam, Mohd Bakri, Ibrahim, Noor Akma

“…The Multiple-try Metropolis (MTM) algorithm is the new alternatives in the field of Bayesian extremes for summarizing the posterior distribution. …”
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Modified Parameters of Harmony Search Algorithm for Better Searching by Nur Farraliza, Mansor, Abas, Z.A, Shibghatullah, A.S., Rahman, A.F.N.A

“…These parameters influence the overall performance of the HS algorithm, and therefore it is crucial to fine-tune them. …”
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Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi by Seyedmehdi, Mirmohammadsadeghi

“…The purpose of this research is to expand the deterministic TTRP models by introducing stochastic parameters to bring these models closer to the reality. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A.

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Ahmed Dheyab, Saad, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Genetic algorithm-based optimal overcurrent relays coordination for standalone sustainable hydrokinetic renewable energy distribution network by Ahmad, Saiful Zuhaimi

“…OCRs depend on its Time Dial Setting (TDS) values which effect the operating time of the relays. This research work propose the artificial intelligent (AI) solution on the objective function (OF) formulation, with the application of genetic algorithm (GA) optimization solver, to determine each relay best optimal operation for the TDS value and response time to fault accordingly and also eliminate miscoordination among the relays. …”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

“…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. To determine the optimum solution in each policy, real coded genetic algorithm is used as an optimization technique. …”
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Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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Generic DNA encoding design scheme to solve combinatorial problems by Rofilde, Hasudungan

“…Using this encoding scheme would enable researchers to solve other hard problems whilst also improving the algorithm.…”
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Feedforward artificial neural network-based model for predicting the removal of phenolic compounds from water by using deep eutectic solvent-functionalized CNTs by Ibrahim R.K., Fiyadh S.S., AlSaadi M.A., Hin L.S., Mohd N.S., Ibrahim S., Afan H.A., Fai C.M., Ahmed A.N., Elshafie A.

Potential fish habitat mapping using MODIS-derived sea surface salinity, temperature and chlorophyll-a data: South China Sea Coastal areas, Malaysia by Daqamseh, Salleh T., Mansor, Shattri, Pradhan, Biswajeet, Billa, Lawal, Mahmud, Ahmad Rodzi

“…Finally, the research has developed a potential fish zone model amalgamating all the above parameters. …”
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Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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Genetic Algorithm based Fuzzy Logic Controller for Optimal Charging-Discharging of Energy Storage in Microgrid applications by Faisal M., Hannan M.A., Ker P.J., Muttaqi K.M.

A review of perovskite solar cell (PSC) : Its revolution and mathematical modelling by Yao, Lee Jin, Rahifa, Ranom, Kyairul Azmi, Baharin, Norhafizah, Md Sarif

“…This paper also summarizes the numerical algorithms and modelling simulations used such as SCAPS, AFORS-HET, COMSOL Multiphysics, MATLAB to evaluate PSC model performance. …”
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Development of cost reduction mathematical model for natural gas transmission network system by Mehrdad, Nikbakht Eliaderany

“…In this research, an Extended Genetic Algorithms (EGA) was investigated to solve the proposed mathematical model and to achieve global or near to global optimum solutions in a reasonable time. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…These results indicated that the proposed models with optimized hyper-parameters produced the accurate classification results. …”
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