Search Results - (( initial solution learning algorithm ) OR ( using optimization based algorithm ))

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

“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
Get full text
Get full text

A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
Get full text
Get full text

Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
Get full text
Get full text
Get full text
Get full text

Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

“…To overcome these problems, two improvements for WOA algorithm are proposed in this paper. The first improvement includes using Elite Opposition-Based Learning (EOBL) at initialization phase of WOA. …”
Get full text
Get full text

Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

“…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
Get full text
Get full text
Get full text
Get full text

Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

“…In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”

Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

“…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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

“…One of these MOO algorithms Multi-Objective Particle Swarm Optimization (MOPSO) extends it to handle problems with multiple objectives simultaneously, but like many swarm-based algorithms, MOPSO can suffer from premature convergence or local optima solutions. …”
Get full text
Get full text
Get full text

Unsupervised Deep Learning Algorithm to Solve Sub-Surface Dynamics for Petroleum Engineering Applications by Kumar, A., Ridha, S., Ilyas, S.U.

“…The solution provided by deep learning for a differential equation is in a closed analytical form which is differentiable and could be used in any subsequent computation. …”
Get full text
Get full text

Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems by Franco, Daniel Jose Da Graca Peceguina

“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
Get full text
Get full text

Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…The latter drawbacks are consequences of the difficulty in balancing the exploration and exploitation processes which directly affect the final quality of the clustering solutions. Hence, this research has proposed three enhanced frameworks, namely, Optimized Gravitational-based (OGC), Density-Based Particle Swarm Optimization (DPSO), and Variance-based Differential Evolution with an Optional Crossover (VDEO) frameworks for data clustering. …”
Get full text
Get full text

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.

“…Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. A modified initialization scheme that leverages grid partitioning and oppositional-based learning is incorporated to produce an evenly distributed initial population across P-V curve. …”

Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…The proposed DNN algorithm is structured to incorporate initial/boundary conditions in cylindrical coordinates and approximate the solution without the aid of any simulated or training data. …”
Get full text
Get full text

Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty by Reza M.S., Hannan M.A., Mansor M.B., Ker P.J., Tiong S.K., Hossain M.J.

“…The proposed method is assessed using aging data from the NASA battery dataset. Its performance is compared with baseline LSTM, baseline GRU, BiLSTM, and LSTM-based particle swarm optimization (PSO) models across various error metrics. …”

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

“…Multilayer Feedforward Back Propagation (MLFFBP) was used. Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
Get full text
Get full text

Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

“…An ensemble of these algorithms is an intelligent and adaptive solution, producing a clean output, while preserving significant pixel information. …”
Get full text
Get full text
Get full text

Orientation and scale based weights initialization scheme for deep convolutional neural networks by Azizi Abdullah, Wong, En Ting

“…A crucial component in the CNN is the convolution filters which consist of a series of predefined filter weight initialization values. The filter weights are then automatically learned by the neural network throughout the back- propagation training algorithm. …”
Get full text
Get full text
Get full text