Search Results - (( pressure distribution free algorithm ) OR ( parameter adoption model algorithm ))*

Peak pressure analysis of foot plantar distribution based on image processing algorithm by Sabry, Ali Hussein

“…The other main goal of this work is to create an algorithm which has the ability to formulate accurately and reliably the distribution of pressure over the foot plantar. …”
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Segment Particle Swarm Optimization Adoption for Large-Scale Kinetic Parameter Identification of Metabolic Network Model by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

“…The seven sensitive kinetic parameters were used in both the algorithms to minimize the model response errors. …”
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Segment particle swarm optimization adoption for large-scale kinetic parameter identification of escherichia coli metabolic network model by Azrag, Mohammed Adam Kunna, Tuty Asmawaty, Abdul Kadir, Jaber, Aqeel S.

“…The seven sensitive kinetic parameters were used in both the algorithms to minimize the model response errors. …”
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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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On determination of input parameters of the mass transfer process by fuzzy approach. by Maan, Normah, Talib, Jamalludin, Arshad, Khairil Annuar, Ahmad, Tahir

“…The algorithm is also capable of determining the optimal values of the input parameters. …”
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Kinetic modelling of free-radical vinyl chloride polymerization with a mixture of initiators by Tan , Amy Siew Wern, Mohd. Yusof, Khairiyah, Hashim, Shahrir

“…The isothermal model predicts the overall monomer conversion, the polymerization rate, reactor pressure and the monomer distribution in the gas, aqueous, and polymer phases for the polymerization cycle. …”
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A comparative study for parameter selection in online auctions by Gan, Kim Soon

“…Self adaptation genetic algorithm is the last model that will be used to evolve the bidding strategy. …”
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Genetic algorithm optimisation for fuzzy control of wheelchair lifting and balancing by Ahmad, Salmiah, Tokhi, M. Osman, Toha, Siti Fauziah

“…Genetic Algorithm is used to control the two-wheeled wheelchair and results show that the optimised parameters give better system performance.…”
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Automatic control of flotation process using computer vision by Saravani, Ali Jahed

“…Finally, a control strategy implementing the developed froth model and prediction system was introduced for direct optimization of metallurgical parameters. …”
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Large-scale kinetic parameters estimation of metabolic model of escherichia coli by Azrag, M. A. K., Tuty Asmawaty, Abdul Kadir, Kabir, M. Nomani, Jaber, Aqeel S.

“…In this work, the PSO algorithm has been adopted to estimate the kinetic parameters by minimizing the errors of the large-scale of metabolic model response of E. coli with reference to real experimental data. …”
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Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Application of memetic algorithm in modelling discrete-time multivariable dynamics systems by Ahmad, Robiah, Jamaluddin, Hishamuddin, Hussain, Mohd. Azlan

“…There are more possible structures to choose from and more parameters are required to obtain a good fit. In this work, a new model structure selection in system identification problems based on a modified GA with an element of local search known as memetic algorithm (MA) is adopted. …”
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Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure by Loo, C.K., Rajeswari, M., Rao, M.V.C.

“…However, GMN is not ergonomic due to too many network control parameters. Therefore, a self-regulating GMN (SGMN) algorithm is proposed. …”
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Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting by Wei Y., Hashim H., Chong K.L., Huang Y.F., Ahmed A.N., El-Shafie A.

“…This study investigated the efficacy of a hybrid model that adopted a meta-heuristic algorithm (MHA) as an optimizer to extend the training ANN method, from a gradient-based to a stochastic population-based approach for streamflow forecasting. …”

Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column by Maan, Normah

“…A series of algorithms in solving the inverse problem were then developed corresponding to the forward models. …”
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Predictive modelling of machining parameters of S45C mild steel by Abbas, Adnan Jameel

“…The artificial neural network type Network Fitting Tool (NFTOOL) is used as a modeling technique for manipulating the ideal algorithm parameters. …”
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Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi by Sherksi, Nasereddin Ibrahim

“…Water distribution systems and their integrity are essential for human life and society. …”
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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

“…The model of constant step function is introduced in the alteration of HMCR parameter. …”
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Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises by Suparman, Suparman, Abdellah Salhi, Abdellah Salhi, Rusiman, Mohd Saifullah

“…After it has worked properly, it was applied to model human heart rate data. The results showed that the MCMC algorithm can estimate the parameters of the MA model. …”
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