Search Results - (( initial study learning algorithm ) OR ( using optimization method algorithm ))

Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…In addition, experiments prove that incremental genetic-based clustering ensemble algorithm speed up to converge into an optimal clustering solution, where pattern ensemble learning method and the cluster partitions produced by the threshold fuzzy c-means clustering algorithm are employed as recombination operator and initial population, respectively.…”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences by Adnan Ashraf, Sobia Pervaiz, Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, Danda B. Rawat

“…To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. …”
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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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Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization by Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Noor Azida, Sahabudin, Nor Bakiah, Abd Warif

“…Estimating parameters values is difficult and time-consuming process due to their highly nonlinear and huge number of kinetic parameters involved. Global optimization method based on an enhanced scatter search (ESS) algorithm is a suitable choice to address this issue. …”
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Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context by Nanna Suryana, Herman, Burairah, Hussin

“…Many algorithms and methods have been proposed for classification problems in bioinformatics. …”
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Improved opposition-based particle swarm optimization algorithm for global optimization by Nafees Ul Hassan, Waqas Haider Bangyal, M. Sadiq Ali Khan, Kashif Nisar, Ag. Asri Ag. Ibrahim, Danda B. Rawat

“…Particle Swarm Optimization (PSO) has been widely used to solve various types of optimization problems. …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

“…Finally, a modified local search method using Perturb and Observe with adaptive step size method (P&O-ASM) is proposed to refine the near-optimal duty cycle and track GMPP with negligible oscillations. …”

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

“…In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

“…In the present study, the solution for the initial condition and boundary value problems in ordinary and partial differential equation by deep learning method have been analyzed. …”
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A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem by Ahmed A.N., Van Lam T., Hung N.D., Van Thieu N., Kisi O., El-Shafie A.

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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Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach by Riska Wahyu, Romadhonia, A'yunin, Sofro, Danang, Ariyanto, Dimas Avian, Maulana, Junaidi Budi, Prihanto

“…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. …”
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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

“…Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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Estimating the un-sampled ph value via neighbouring points using multi-layer neural network - genetic algorithm by Muhammad Aznil, Ab Aziz, Mohammad Fadhil, Abas, Muhamad Abdul Hasib, Ali, Norhafidzah, Mohd Saad, Mohd Hisyam, Ariff, Mohamad Khairul Anwar, Abu Bashrin

“…In investigating this method, three algorithms are used: Neural Network-Genetic Algorithm (MLNN-GA), MLNN with backpropagation (MLNN-BP), and averaging method. …”
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CUCKOO SEARCH OPTIMIZATION NEURAL NETWORK MODELS FOR FORECASTING LONG-TERM PRECIPITATION by Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman, Khairul Anwar, Mohamad Said

“…This paper presents the application of a novel optimization algorithm, Cuckoo Search Optimization (CSO), to train feedforward neural networks to forecast long-term precipitation using three climate models, namely HadCM3, ECHAM5, and HadGEM3‐RA. …”
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A Study on Abstract Policy for Acceleration of Reinforcement Learning by Ahmad Afif, Mohd Faudzi, Hirotaka, Takano, Junichi, Murata

“…Reinforcement learning (RL) is well known as one of the methods that can be applied to unknown problems. However, because optimization at every state requires trial-and-error, the learning time becomes large when environment has many states. …”
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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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Optimization-driven extreme learning machine for floating photovoltaic power prediction: A teaching learning-based approach by Mohd Redzuan, Ahmad, Nor Farizan, Zakaria, Mohd Shawal, Jadin, Mohd Herwan, Sulaiman

“…This study presents a novel Teaching–Learning-Based Optimization enhanced Extreme Learning Machine (TLBO-ELM) framework that achieves optimal parameter configuration without algorithmic tuning while maintaining computational efficiency for real-time deployment. …”
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