Search Results - (( using optimization based algorithm ) OR ( variable enhancing learning algorithm ))

Enhancing wind power forecasting accuracy with hybrid deep learning and teaching-learning-based optimization by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…Metaheuristic algorithms including Particle Swarm Optimization (PSO), Barnacles Mating Optimizer (BMO), Biogeography-Based Optimization (BBO), and Firefly Algorithm (FA) are comprehensively compared for model optimization. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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Fuzzy based BSA optimization for maximum power point tracking controller performance evaluation by Sayem M.A., Nadzirah A., Al-Shetwi A.Q., Hannan M.A., Ker P.J., Rahman S.A., Muttaqi K.M.

Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness by Noori, Mustafa Sabah, Sahbudin, Ratna K.Z., Sali, Aduwati, Hashim, Fazirulhisyam

“…Many machine learning algorithms excel at handling problems with conflicting objectives. …”
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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.

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

Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach by Khan, Arshad Ali, Mazlina, Abdul Majid, Dandoush, Abdulhalim

“…The convolutional neural network is optimized using genetic algorithms, which dynamically tune hyperparameters such as learning rate, batch size, and momentum to improve performance and generalizability across diverse environmental conditions. …”
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

“…Also, the model performance was characterized based on the number of input variables utilized. …”

Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
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Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Dele-Afolabi T.T., Ahmadipour M., Azmah Hanim M.A., Oyekanmi A.A., Ansari M.N.M., Sikiru S., Kumar N.

“…An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”

Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Temitope T., Dele-Afolabi, Masoud, Ahmadipour, Mohamed Ariff, Azmah Hanim, A.A., Oyekanmi, M.N.M., Ansari, Sikiru, Surajudeen, Kumar, Niraj

“…An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”
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Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab by Saad Mawlood , Saab

“…The research improved the predictive models by integrating them with the Genetic Algorithm (GA). The optimizer algorithm (i.e., GA) determines the optimal input variables and internal parameters in the prediction models. …”
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DeMI interface tool for profit estimation and waste conversion technology recommendations in enhancing municipal solid waste management by Ali, R.A., Nik Ibrahim, N.N.L., Ghani, W.A.W.A.K., Sani, N.S., Lam, H.L.

“…The M5P algorithm, adept at profit estimation, establishes correlations between MSW weight and profitability, while the J48 algorithm offers recommendations for suitable waste conversion technologies based on profit potential. …”
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Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers by Siaw Hui, Teo

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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

“…Two new adaptive routing algorithms named Enhanced Confidence-based Q (ECQ) and Enhanced Confidence-based Dual Reinforcement Q (ECDRQ) Routing Algorithms are proposed in this thesis. …”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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