Search Results - (( parameter evaluation method algorithm ) OR ( using simulation learning algorithm ))

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.

“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”

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.

Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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Deep Learning Based image segmentation for expensive soil desiccation crack recognition and qualification by Ling, Hui Yean

“…This study investigated the feasibility and effectiveness of image-based techniques using advanced deep learning algorithms to quantify desiccation cracks in expansive soils. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…The NPO is inspired by the lifestyle of the nomads. The proposed algorithm simulates the behavior of the nomads when they are searching for life sources (water or grazing fields). …”
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A genetically trained adaptive neuro-fuzzy inference system network utilized as a proportional-integral-derivative-like feedback controller for non-linear systems. by Lutfy, Omar Farouq, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Ali Abbas, Kassim

“…Three important issues are addressed in this paper, which are, first, the evaluation of the ANFIS as a PID-like controller; second, the utilization of the GA (genetic algorithm) alone to train the ANFIS controller, instead of the hybrid learning methods that are widely used in the literature; and, third, the determination of the input and output scaling factors for this controller by the GA. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…The proposed method involves using a convolutional neural network (CNN) with a feature extraction ability to learn from the hydrological dataset efficiently. …”
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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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Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques by Anifowose, Fatai Adesina

“…Common metrics were used to evaluate the performance of the proposed models. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki by Mahmoud, Khaki

“…These results confirm that, for all the networks the Levenberg-Marquardt algorithm is the most effective algorithm to model the groundwater level. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

“…In order to study the numerical simulation of the measured data for a given subsurface parameter, the basis of the finite difference method and the various boundary conditions are explained here. …”
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Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

“…The objective of this paper is to introduce a combination of advantages of different algorithm scheme into one learning algorithm. For this purpose, three models is developed, first using recursive least square algorithm (RLS), second using recursive instrument variable (RIV) algorithm and lastly using combination of this two algorithms. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

“…Due to network complexity, conventional QoS-improving routing algorithms (RAs) may be impractical. Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”

Octane number prediction for gasoline blends using convolution neural network / Zhu Yue by Zhu , Yue

“…In the project three commonly use algorithm are used for prediction of octane number for gasoline blends, which describes the behavior of the fuel in the engine at lower temperatures and speeds, and is an attemp to simulate acceleration behavior.These tree algorithm are back propagation (BP), radial basis funtion (RBF) and Extreme learning machine (ELM) algorithm. …”
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Prediction of Total Maximum Daily Loads (TMDLs) of pollutants in river by using artificial neural network (ANN) / Khairunnisa Khairudin, Mohamed Syazwan Osman and Syahrul Fithry Se... by Khairudin, Khairunnisa, Osman, Mohamed Syazwan, Senin, Syahrul Fithry

“…The learning algorithm used is Bayesian Regularization with tansig transfer function at the hidden layer and purelin transfer function at the output layer. …”
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