Search Results - (( parameter optimization learning algorithm ) OR ( wave optimization model algorithm ))

An inclusive multiple model for predicting total sediment transport rate in the presence of coastal vegetation cover based on optimized kernel extreme learning models by Jalil-Masir H., Fattahi R., Ghanbari-Adivi E., Asadi Aghbolaghi M., Ehteram M., Ahmed A.N., El-Shafie A.

Artificial Neural Network Based Particle Swarm Optimization for Microgrid Optimal Energy Scheduling by Abdolrasol M., Mohamed R., Hannan M., Al-Shetwi A., Mansor M., Blaabjerg F.

Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems by Manap, Zahariah

“…The key attributes that establish the classification learning sessions are the channel parameters extracted from the ray tracing generated multipath signals. …”
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Pipeline scour rates prediction-based model utilizing a multilayer perceptron-colliding body algorithm by Ehteram M., Ahmed A.N., Ling L., Fai C.M., Latif S.D., Afan H.A., Banadkooki F.B., El-Shafie A.

“…Forecasting; Multilayers; Particle swarm optimization (PSO); Pipelines; Soft computing; Colliding bodies; MLP model; Multi layer perceptron; Optimization algorithms; Optimization modeling; Prediction model; Soft computing models; Wave characteristics; Scour; algorithm; hydrological modeling; model; optimization; pipeline; scour; Cetacea…”

Inversion Of Surface Wave Phase Velocity Using New Genetic Algorithm Technique For Geotechnical Site Investigation by Hamimu, La

“…Therefore the use of genetic algorithm (GA) optimization technique which is one of nonlinear optimization methods is an appropriate choice to solve surface wave inversion problem having high nonlinearity and multimodality. …”
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Healthcare Data Analysis Using Water Wave Optimization-Based Diagnostic Model by Kaur, Arvinder, Kumar, Yugal

“…This paper presents a new diagnostic model for various diseases. In the proposed diagnostic model, a water wave optimization (WWO) algorithm was implemented for improving the diagnosis accuracy. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction by Alqushaibi, A., Abdulkadir, S.J., Rais, H.M., Al-Tashi, Q., Ragab, M.G., Alhussian, H.

“…Therefore, the wind plays an essential role in the oceanic atmosphere and contributes to the formation of waves. This paper proposes an enhanced weight-optimized neural network based on Sine Cosine Algorithm (SCA) to accurately predict the wave height. …”
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Water wave optimization with deep learning driven smart grid stability prediction by Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, Alamgeer, Mohammad, K. Nour, Mohamed, Abdelrahman, Anas, Motwakel, Abdelwahed

“…In this background, the current study introduces a novel Water Wave Optimization with Optimal Deep Learning Driven Smart Grid Stability Prediction (WWOODL-SGSP) model. …”
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Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…This paper proposes optimal parameters for an extreme learning machine-based interval type 2 fuzzy logic system to learn its best configuration. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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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.

“…Although this algorithm is optimal for the parameters which appear linearly in the consequent part of interval type-2 fuzzy logic systems, it is not optimal for the parameters of the antecedent part as it uses random parameters. …”
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A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

“…The learning phase of wavelet neural network entails the task of finding the optimal set of parameter, which includes wavelet activation function, translation centers, dilation parameter, synaptic weight values, and bias terms. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

“…Many variants have been developed to cope with this problem and improve algorithm performance. In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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Artificial bee colony optimization of interval type-2 fuzzy extreme learning system for chaotic data by Hassan, S., Jaafar, J., Khanesar, M.A., Khosravi, A.

“…This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed hybrid learning algorithm utilizes the combination of extreme learning machine (ELM) and artificial bee colony optimization (ABC) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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Efficient Numerical Modelling of Extreme Wave by Tan , Vi Nie

“…The performance of the OceanWave 3D model under different wave cases had been identified to understand the efficiency of the model. …”
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Efficient Numerical Modelling of Extreme Waves by Tan, Vi Nie

“…The performance of the OceanWave 3D model under different wave cases had been identified to understand the efficiency of the model. …”
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