Search Results - (( based optimization method algorithm ) OR ( learning adaptation optimization algorithm ))

Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

“…The method is compared to the existing optimization methods in machine learning, namely stochastic gradient descent method (SGD) and Adam. …”
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A memory-based gravitational search algorithm for enhancing minimum variance distortionless response beamforming by Darzi S., Sieh Kiong T., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

“…Algorithms; Artificial intelligence; Beamforming; Benchmarking; Heuristic algorithms; Iterative methods; Learning algorithms; Particle swarm optimization (PSO); Adaptive Beamforming; Gravitational search algorithm (GSA); Gravitational search algorithms; Heuristic optimization algorithms; Minimum variance distortionless response; Optimal trajectories; Optimization problems; Real-world optimization; Optimization…”

Adaptive route optimization for mobile robot navigation using evolutionary algorithm by Kit Guan Lim, Guan Lim, Yoong Hean Lee, Hean Lee, Min Keng Tan, Keng Tan, Hou, Pin Yoong, Tienlei, Wang, Tze, Kenneth Kin Teo

“…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training by Lee, Sen Tan, Zainuddin, Zarita, Ong, Pauline

“…To evaluate the performance of the proposed IBOA training method, the obtained results are compared to the results of the momentum backpropagation (MBP), the particle swarm optimization (PSO) and the standard butterfly optimization algorithm (BOA) training methods. …”
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

“…In the experiment, we conducted an evaluation of the effectiveness and efficiency of four nature-inspired binary algorithms for optimization namely Binary Particle Swarm Optimization (BPSO), Binary Grey Wolf Optimization algorithm (BGWO), Binary Differential Evolution algorithm (BDE), and Binary Salp Swarm algorithm (BSS) - in the context of human activity recognition (HAR). …”
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A review of training methods of ANFIS for applications in business and economic by Mohd Salleh, Mohd Najib, Hussain, Kashif

“…Moreover, the standard gradient based learning via two pass learning algorithm is prone slow and prone to get stuck in local minima. …”
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An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting by Mohd Redzuan, Ahmad, Nor Farizan, Zakaria, Mohd Shawal, Jadin, Mohd Herwan, Sulaiman

“…This study presents an improved teaching-learning-based optimization algorithm with extreme learning machine for floating photovoltaic power forecasting. …”
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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. …”
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A review of training methods of ANFIS for applications in business and economics by Mohd Salleh, Mohd Najib, Hussain, Kashif

“…Moreover, the standard gradient based learning via two pass learning algorithm is prone slow and prone to get stuck in local minima. …”
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A novel hybrid photovoltaic current prediction model utilizing singular spectrum analysis, adaptive beluga whale optimization, and improved extreme learning machine by Mohammed Ridha, Hussein, Ahmadipour, Masoud, Alghrairi, Mokhalad, Hizam, Hashim, Mirjalili, Seyedali, Zubaidi, Salah L., Mohammed S, Marwa Y.

“…This paper introduces a novel prediction hybrid model based on singular spectrum analysis (SSA), adaptive beluga whale optimization (ABWO), and an improved extreme learning machine (IELM). …”
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Design and optimization of a test case generation algorithm for real-time embedded systems based on adaptive Q-Learning by Yingbei, Niu, Chai, Soo See

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Predicting the classification of heart failure patients using optimized machine learning algorithms by Ahmed, Marzia, Mohd Herwan, Sulaiman, Hassan, Md Maruf, Bhuiyan, Touhid

“…This study proposes an optimized machine learning approach using Gradient Boosting Machine (GBM) and Adaptive Inertia Weight Particle Swarm Optimization (AIWPSO) to predict heart failure survival. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

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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. …”

New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks by Marzia, Ahmed

“…Secondly, this thesis invents the new bio-inspired Gooseneck Barnacle Optimization Algorithm (GBO), drawing inspiration from gooseneck barnacle mating behaviors, to address the limitations of the original BMO and its variants, aiming for more realistic and robust optimization. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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Feedforward neural network for solving particular fractional differential equations by Admon, Mohd Rashid

“…This research aims to develop a scheme based on a feedforward neural network (FNN) with a vectorized algorithm (FNNVA) for solving FDEs in the Caputo sense (FDEsC) using selected first-order optimization techniques: simple gradient descent (GD), momentum method (MM), and adaptive moment estimation method (Adam). …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

“…This adaptive algorithm can thus be applied to any e-learning platform for optimal content delivery to its users in real-time. © 2014 IEEE.…”