Search Results - (( model relation between algorithm ) OR ( based optimization means algorithms ))*

Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…Therefore, this article identified various continuous-time Hammerstein models based on an improved Archimedes optimization algorithm (IAOA) to address these concerns. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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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

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Enhanced long short-term memory with fireworks algorithm and mutation operator by Changqing Gong, Xinyao Wang, Abdullah Gani, Han Qi

“…Aiming at the problems of lower predictive accuracy and slower convergent speed of the existing prediction models, a prediction model based on fireworks algorithm (FWA) and long short-term memory (LSTM) is proposed to predict time-related data. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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Stock price predictive analysis: An application of hybrid barnacles mating optimizer with artificial neural network by Zuriani, Mustaffa, Mohd Herwan, Sulaiman

“…As a relatively new optimization algorithm, it has been shown to be effective in addressing various optimization problems. …”
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Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms by Fard Masoumi, Hamid Reza

“…In this regard, the related parameters of developed model were determined by applying chemometrics techniques on the experimental data. …”
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Stock price predictive analysis : An application of hybrid barnacles mating optimizer with artificial neural network by Zuriani, Mustaffa, Mohd Herwan, Sulaiman

“…As a relatively new optimization algorithm, it has been shown to be effective in addressing various optimization problems. …”
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Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization by M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.

“…Based on the optimization results, the MFO outperformed other comparison algorithms for the mean fitness and also the best fitness. …”
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Ant colony optimization and genetic algorithm models for suspended sediment discharge estimation for gorgan-river, Iran by Mohammad Reza Pour, Omolbani

“…Therefore, it is still necessary to develop the model for the discharge-sediment relationship. New models based on artificial intelligence models, namely; Ant Colony Optimization (ACO) and Genetic Algorithm (GA) are now being used more frequently to solve optimization problems. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…A similar degree between points was utilized to get similarity density, and then by means of maximum density points selecting them as weights of the Kohonen algorithm. …”
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Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region by Anees, Shoaib Ahmad, Mehmood, Kaleem, Khan, Waseem Razzaq, Sajjad, Muhammad, Alahmadi, Tahani Awad, Alharbi, Sulaiman Ali, Luo, Mi

“…This conclusion was reached by assessing its outstanding performance when compared to an independent validation dataset. The RF model exhibited remarkable accuracy, presenting relative mean absolute error (RMAE), relative root mean square error (RRMSE), and R2 values of 14.33%, 22.23%, and 0.81, respectively. …”
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Membership function model for defining optimality of vapor pressure deficit in closed-field cultivation of tomato by Shamshiri, Ramin, Che Man, Hasfalina, Zakaria, Abd Jamil, Beveren, Peter van, Wan Ismail, Wan Ishak, Ahmad, Desa

“…An incremental algorithm was written in MATLAB© based on definitive concepts in VPD equations and the GR model. …”
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Optimization of transesterification process for Ceiba pentandra oil: A comparative study between kernel-based extreme learning machine and artificial neural networks by Kusumo F., Silitonga A.S., Masjuki H.H., Ong H.C., Siswantoro J., Mahlia T.M.I.

Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings by Homod R.Z., Gaeid K.S., Dawood S.M., Hatami A., Sahari K.S.

Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…Hence, RX-STPM becomes an optimal equilibrium between exploration and exploitation strategies in leading the system towards global optima. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…Single-objective optimization improves the validity of the model by minimizing the mean square error (MSE) between the experimental data and the prediction with the adjustment of the input values of the model parameters. …”
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Enhanced recognition methods for text and slider CAPTCHA vulnerability assessment by Xing, Wan

“…By comparing them with the benchmark models in terms of recognition accuracy, precision, computational complexity, storage space, and other metrics, the superiority of our proposed algorithm is proved. …”
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Hand, Foot and Mouth Disease (HFMD)'s Hotspot Identification using Bipartite Network Model by Nor Shamira, Sabri

“…The location nodes in the targeted and validated models were ranked using the web-based search algorithms according to the respective ranking values. …”
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Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq by Yaseen, Z.M., Jaafar, O., Deo, R.C., Kisi, O., Adamowski, J., Quilty, J., El-Shafie, A.

“…The forecasting metrics defined as the correlation coefficient (r), Nash-Sutcliffe efficiency (ENS), Willmott's Index (WI), root-mean-square error (RMSE) and mean absolute error (MAE) computed between the observed and forecasted stream-flow data are employed to assess the ELM model's effectiveness. …”
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