Search Results - (( model validating ((a algorithm) OR (bat algorithm)) ) OR ( carlo simulation based algorithm ))

Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

“…Secondly, two meta-heuristics, namely, Bi-Objective Gravitational Search Algorithm (BOGSA) and Bi-Objective Bat Algorithm (BOBAT), were combined to form a (BOGS-BAT) algorithm. …”
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SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

“…Its performance is assessed using Monte Carlo simulation experiments based on five specification models, three strengths of correlation disturbances and two sample sizes. …”
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Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin

“…The fuzzy models are trained applying locally linear model tree algorithm followed by a meta-heuristic nature inspired algorithm called bat algorithm. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”

A hybrid bat�swarm algorithm for optimizing dam and reservoir operation by Yaseen Z.M., Allawi M.F., Karami H., Ehteram M., Farzin S., Ahmed A.N., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., El-Shafie A.

A hybrid bat–swarm algorithm for optimizing dam and reservoir operation by Yaseen, Zaher Mundher, Allawi, Mohammed Falah, Karami, Hojat, Ehteram, Mohammad, Farzin, Saeed, Ahmed, Ali Najah, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, El-Shafie, Ahmed

“…This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). …”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia by Wee W.J., Chong K.L., Ahmed A.N., Malek M.B.A., Huang Y.F., Sherif M., Elshafie A.

“…The bat algorithm (BA), a meta-heuristic approach, was used in this study to optimize the weights and biases of the artificial neural network (ANN) model. …”

New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

“…Thirdly, the thesis validates the algorithm's performance on standard constrained single objective and multi objective benchmark test functions. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…The performance of the algorithm is validated with experimental datasets. …”
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Bat optimization algorithm with fuzzy based PIT sharing (BF-PIT) algorithm for Named Data Networking (NDN) by Uma Maheswari P., Manickam P., Sathesh Kumar K., Maseleno A., Shankar K.

Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

“…To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”

Cluster-based spectrum sensing scheme in heterogeneous network by Hasan M.K., Ismail A.F., Abdalla A.-H., Ramli H.A.M., Islam S., Hashim W., Badron K.

Long-term optimal planning of distributed generations and battery energy storage systems towards high integration of green energy considering uncertainty and demand response progra... by Ba-swaimi S., Verayiah R., Ramachandaramurthy V.K., ALAhmad A.K.

“…To solve the proposed model, a hybrid approach combining Non-Dominated Sorting Genetic Algorithm II (NSGAII) and Multi-Objective Particle Swarm Optimization (MOPSO) is employed. …”

Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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Class-based storage assignments for miniload AS/RS with open-rack structure by Vasili, M. R., Tang, Sai Hong, Ismail, Napsiah, Sulaiman, Shamsuddin

“…The travel time model and the performance of proposed AS/RS are validated using Monte Carlo simulation and are compared with a conventional one. …”
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Multi depot dynamic vehicle routing problem with stochastic road capacity for emergency medical supply delivery in humanitarian logistics by Anuar, Wadi Khalid

“…Based on the chaotic setting from a disaster event, the model and solution proposed are validated and analysed through a Decision Support System (DSS), MDDVRPSRC DSS. …”
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Subspace Techniques for Brain Signal Enhancement by Kamel , Nidal, Yusoff, Mohd Zuki

“…Next, the validity and the effectiveness of the algorithms to detect the P100's (used in objective assessment of visual pathways) are evaluated using real patient data collected from a hospital. …”
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Cluster-based spectrum sensing scheme in heterogeneous network by Hasan, Mohammad Kamrul, Ismail, Ahmad Fadzil, Hassan Abdalla Hashim, Aisha, Mohd. Ramli, Huda Adibah, Hashim, Wahidah, Islam, Shayla, Badron, Khairayu

“…The perfor-mance of the proposed scheme is evaluated in Monte Carlo simulation validate the scheme performance.…”
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Cluster-based spectrum sensing scheme in heterogeneous network by Hasan, Mohammad Kamrul, Ismail, Ahmad Fadzil, Mohd. Ramli, Huda Adibah, Hassan Abdalla Hashim, Aisha, Islam, Shayla, Hashim, Wahidah, Badron, Khairayu

“…The performance of the proposed scheme is evaluated in Monte Carlo simulation validate the scheme performance…”
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Investigation on the potential to integrate different artificial intelligence models with metaheuristic algorithms for improving river suspended sediment predictions by Ehteram M., Ghotbi S., Kisi O., Ahmed A.N., Hayder G., Fai C.M., Krishnan M., Afan H.A., EL-Shafie A.

“…Although the adaptive neuro fuzzy system (ANFIS) and multilayer feed-forward neural network (MFNN) have been widely used to simulate hydrological variables, improving the accuracy of the above models is an important issue for hydrologists. In this article, the ANFIS and MFNN models were improved by the bat algorithm (BA) and weed algorithm (WA). …”