Search Results - (( using factorization learning algorithm ) OR ( parameter optimization model algorithm ))

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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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

“…The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”

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.

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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

“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…The study also introduces a novel optimization algorithm for selecting inputs. While the LSSVM model may not capture nonlinear components of the time series data, the extreme learning machine (ELM) model�MKLSSVM model can capture nonlinear and linear components of the time series data. …”

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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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…This approach was based on fuzzy expert system (FES) using Fuzzy Toolbox of MATLAB software. Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Ayob A., Saad M.H.M., Muttaqi K.M.

Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”

Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan by Adenan, Muhammad Nasrul Hakim

“…The ANN model performance can be optimized by altering certain parameters in the learning algorithm. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli by Hakim Adenan, Muhammad Nasrul, Zolkapli, Maizatul

“…The ANN model performance can be optimized by altering certain parameters in the learning algorithm. …”
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Predictive modelling of nanofluids thermophysical properties using machine learning by Olanrewaju, Alade Ibrahim

“…The optimization of the machine learning parameters was conducted using the Genetic Algorithm or the Bayesian Optimization Algorithm techniques. …”
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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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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

“…In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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Analysis of online CSR message authenticity on consumer purchase intention in social media on Internet platform via PSO-1DCNN algorithm by Li, Man, Liu, Fang, Abdullah, Zulhamri

“…Secondly, this work designs optimization measures from inertia weight and learning factor to build an improved particle swarm optimization algorithm (IPSO). …”
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Machine learning algorithm as a sustainable tool for dissolved oxygen prediction: a case study of Feitsui Reservoir, Taiwan by Ziyad Sami B.F., Latif S.D., Ahmed A.N., Chow M.F., Murti M.A., Suhendi A., Ziyad Sami B.H., Wong J.K., Birima A.H., El-Shafie A.

Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi by Hayawi, Mustafa Jabbar

“…EHA are known to have nonlinear parameters and dynamic factors such as frictions, load variations and leakage. …”
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Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

“…The result indicates the performance of the optimized model outperforms the baseline model.…”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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