Search Results - (( using evolution method algorithm ) OR ( parameters optimization approach algorithm ))

Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
Get full text
Get full text
Get full text

Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

“…Other metaheuristic approaches such as genetic algorithm, differential evolution algorithm, particle swarm optimization, and ant colony optimization are still preferable to address combinatorial optimization problems. …”
Get full text
Get full text
Get full text
Get full text

Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

“…Interestingly, the manipulator's behaviours using the spiral dynamics algorithm for PID controller tuning were superior to those using alternative methods. …”
Get full text
Get full text
Get full text

Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks by Hussein, Yassein Soubhi

“…The results demonstrated that our proposed method results in significant reductions of HOF, HOPP and packet loss ratio (PLR) compared to the conventional HHO and enhanced weighted performance HO parameter optimization (EWPHPO) algorithm. …”
Get full text
Get full text

Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

“…The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
Get full text
Get full text
Get full text

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
Get full text
Get full text
Get full text

Novel farmland fertility algorithm based PIDPSS design for SMIB angular stability enhancement by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi, Mohd Jaffar, Mai Zurwatul Ahlam

“…A new metaheuristics method called Farmland Fertility Algorithm (FFA) inspired by nature is proposed for optimal design of PIDPSS using a robust ISTSE objective function which had to be minimized. …”
Get full text
Get full text
Get full text

An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines by Bala, A., Ismail, I., Ibrahim, R., Sait, S.M., Oliva, D.

“…This problem is often formulated as a typical optimization problem. Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
Get full text
Get full text

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
Get full text
Get full text
Get full text

Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

“…The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. …”
Get full text
Get full text
Get full text

Solving an application of university course timetabling problem by using genetic algorithm by Norhana, Shaibatul Khadri

“…Among the approaches, genetic algorithm (GA), constructed based on Darwin's theory of evolution, becomes the renowned approach to solve various types of timetabling problems. …”
Get full text
Get full text
Get full text

Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons by Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C., El-Shafie, Ahmed

“…In this study, the uncertainty and nonstationary characteristics of streamflow data has been treated using a set of coupled data pre-processing methods before being considered as input for an artificial neural network algorithm namely; rolling mechanism (RM) and grey models (GM). …”
Get full text
Get full text

A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

“…In addition, to enhance the performance teaching learning-based artificial bee colony (TLABC) method has been used at distinct weather conditions. …”
Get full text
Get full text

Evaluation and prediction of time overruns in Jordanian construction projects using coral reefs optimization and deep learning methods by Shihadeh, Jumana, Al-Shaibie, Ghyda, Bisharah, Majdi, Alshami, Dania, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…This study aimed to utilize deep learning, specifically the Multi-Layer Perceptron (MLP), and enhance its overrun predictive ability by incorporating the Coral Reefs Optimization Algorithm (CROA). The approach employed in our study involved the utilization of a comprehensive dataset encompassing diverse aspects of building projects, ranging from financial indicators to project durations. …”
Get full text
Get full text

Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem by Tuani Ibrahim, Ahamed Fayeez, Keedwell, Edward, Collett, Matthew

“…The majority of optimization algorithms require proper parameter tuning to achieve the best performance. …”
Get full text
Get full text
Get full text
Get full text

PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
Get full text
Get full text

Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences by Leong, Wah June, Sie, Long Kek, Teo, Kok Lay, Sim, Sy Yi

“…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
Get full text
Get full text
Get full text

Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

“…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
Get full text
Get full text
Get full text

Machining optimization using Firefly Algorithm / Farhan Md Jasni by Md Jasni, Farhan

“…Based on the previous research on the success of Firefly Algorithm, this approach will be able to optimize the machining parameter of milling operation. …”
Get full text
Get full text

Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
Get full text
Get full text
Get full text