Search Results - (( simulation optimization method algorithm ) OR ( using computational learning algorithm ))

Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

“…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”

Opposition- based simulated kalman filters and their application in system identification by Kamil Zakwan, Mohd Azmi

“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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Hybrid Henry Gas-Harris Hawks comprehensive-opposition algorithm for task scheduling in cloud computing by Omran Alkaam, Nora, Md Sultan, Abu Bakar, Hussin, Masnida, Yatim Sharif, Khaironi

“…This method is based on two elements: comprehensive opposition-based learning (COBL) and Harris Hawks Optimization (HHO). …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. …”

Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization by Yap, David F. W., Koh, S. P., Tiong, S. K.

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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

“…This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. …”
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Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

“…In the present study, the solution for the initial condition and boundary value problems in ordinary and partial differential equation by deep learning method have been analyzed. The propsed algorithm could be valuable aid for analyzing the fluid flow and reservoir simulation in an effective manner. …”
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Deep reinforcement learning online offloading for SWIPT multiple access edge computing network by Teckchai, Tiong, Ismail Saad, Tze, Kenneth Kin Teo, Herwansyah Lago

“…Simulation results are presented to demonstrate that the proposed algorithm is able to approach near-optimal performance and superior in decreasing tasks computation time compared with existing optimization methods, enabling real time optimal resource allocation and offloading achievable in a fast-fading wireless environment.…”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Optimal null steering of minimum variance distortionless response adaptive beamforming using particle swarm optimization and gravitational search algorithm by Darzi S., Tiong S.K., Islam M.T., Ismail M., Kibria S.

A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Saleh, Basma Jumaa, Omar, Zaid, As’ari, Muhammad Amir, Bhateja, Vikrant, Izhar, Lila Iznita

“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter by Badaruddin, Muhammad, Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Ahmad Afif, Mohd Faudzi, Pebrianti, Dwi

“…The performance of SMOPE has been tested using particle swarm optimization (PSO) and gravitational search algorithm. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

“…The dataset development for both algorithms is carried out via simulations in Graphical Network Simulator 3 (GNS3). …”

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.

“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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