Search Results - (( evolution optimization mead algorithm ) OR ( _ practical function algorithm ))

Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm by Ling, Kuok Fong, Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

“…The proposed PID controller, optimized using AOA, is contrasted with PID controllers tuned via alternative algorithms including the hybrid Nelder-Mead method (AEONM), artificial ecosystem-based optimization (AEO), differential evolution (DE), and particle swarm optimizer (PSO). …”
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Enhancing speed performance of the cryptographic algorithm based on the lucas sequence by M. Abulkhirat, Esam

“…The deployment of network security procedures requires the implementation of cryptographic functions. More specifically, these include encryption, decryption, authentication, digital signature algorithms and message-digest functions. …”
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Biological-based semi-supervised clustering algorithm to improve gene function prediction by Kasim, Shahreen, Deris, Safaai, M. Othman, Razib, Hashim, Rathiah

“…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

“…The NLFXLMS algorithm is a stochastic gradient algorithm that incorporates the derivative of a nonlinear plant model which is represented by the scaled error function (SEF) in the controller design. …”
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A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408) by Woon, Siew Fang, Karim, Sharmila, Mohamad, Mohd Saiful Adli

“…Then, we tested the proposed method on several benchmark test problems, such as Colvilles function, Goldstein and Prices function, Beales function, Powells function, and Rosenbrocks function. …”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

“…Although the practicability of using wavelet neural networks (WNNs) in nonlinear function approximation has been addressed extensively, selecting the optimal number of hidden nodes and their appropriate initial locations remains a great challenge for WNNs’ initialization. …”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

“…Although the practicability of using wavelet neural networks (WNNs) in nonlinear function approximation has been addressed extensively, selecting the optimal number of hidden nodes and their appropriate initial locations remains a great challenge for WNNs’ initialization. …”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

“…Although the practicability of using wavelet neural networks (WNNs) in nonlinear function approximation has been addressed extensively, selecting the optimal number of hidden nodes and their appropriate initial locations remains a great challenge for WNNs’ initialization. …”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

“…Although the practicability of using wavelet neural networks (WNNs) in nonlinear function approximation has been addressed extensively, selecting the optimal number of hidden nodes and their appropriate initial locations remains a great challenge for WNNs’ initialization. …”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

“…Although the practicability of using wavelet neural networks (WNNs) in nonlinear function approximation has been addressed extensively, selecting the optimal number of hidden nodes and their appropriate initial locations remains a great challenge for WNNs’ initialization. …”
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An optimized wavelet neural networks using cuckoo search algorithm for function approximation and chaotic time series prediction by Pauline Ong, Pauline Ong, Zainuddin, Zarita

“…Although the practicability of using wavelet neural networks (WNNs) in nonlinear function approximation has been addressed extensively, selecting the optimal number of hidden nodes and their appropriate initial locations remains a great challenge for WNNs’ initialization. …”
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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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A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

“…This will make the learning process simpler and more convenient in practice. Moreover, GRBF trained by the new algorithm has an apparent statistical meaning. …”
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Modified Firefly Algorithm in Solving Economic Dispatch Problems with Practical Constraints by M. H., Sulaiman

“…This paper presents a modified Firefly Algorithm (MFA) for solving economic dispatch (ED) problems. …”
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Monotone Fuzzy Rule Interpolation for Practical Modeling of the Zero-Order TSK Fuzzy Inference System by Kai Meng, Tay, Yi Wen, Kerk, Chee Peng, Lim

“…The proposed MFRI algorithm aims to achieve an ε -optimality condition and to produce an ε -optimal solution, which is geared for practical applications. …”
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A new cryptosystem analogous to LUCELG and Cramer-Shoup by Muslim, Norliana, Md. Said, Mohamad Rushdan

“…Cramer-Shoup is a practical public key cryptosystem provably secure against adaptive chosen ciphertext attack that requires a universal one-way hash function. …”
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Adaptable algorithms for performance optimization of dynamic batch manufacturing processes by Teo, Kenneth Tze Kin

“…The idea is proposed in an effort of accessing the functionality and practicability of the dynamic optimizer for the purpose of precision optimization. …”
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A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control by Ahmad, Mohd Ashraf, Izci, Davut, Ekinci, Serdar, Mohd Tumari, Mohd Zaidi

“…The performance of the proposed approach was extensively benchmarked against four modern metaheuristic algorithms (greater cane rat algorithm, catch fish optimization algorithm, RIME algorithm and artificial hummingbird algorithm) under identical conditions. …”
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Nonlinear THF-FXLMS algorithm for active noise control with loudspeaker nonlinearity by Ghasemi, Sepehr, Raja Ahmad, Raja Mohd Kamil, Marhaban, Mohammad Hamiruce

“…In this work, the NLFXLMS algorithm is modified by incorporating the tangential hyperbolic function (THF) to model the saturation effect of the loudspeaker. …”
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Comparing alternative methods for improving the bisection techniques: modified bracketing method and Regula Falsi Algorithm / Nurul Ain Syafika Juperi, Nur Yasmin Hanani Mahdiber a... by Juperi, Nurul Ain Syafika, Mahdiber, Nur Yasmin Hanani, Khairul Nizam, Amylia Natasha

“…Then, some selected test functions are applied into the Bisection Method, Modified Bracketing Method and Regula Falsi Algorithm to decide which is the most practical method. …”
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