Search Results - (( basic selection method algorithm ) OR ( using optimization method algorithm ))

A hybrid particle swarm optimization approach and its application to solving portfolio selection problems by Shamshul Bahar, Yaakob, Prof. Madya, Watada, Junzo

Get full text

An ensemble feature selection method to detect web spam by Oskouei, Mahdieh Danandeh, Razavi, Seyed Naser

“…Web spam is an illegal method to increase mendacious rank of internet pages by deceiving the algorithms of search engines, so it is essential to use an efficient method. …”
Get full text
Get full text
Get full text

Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

Backtracking search algorithm for optimal power dispatch in power system / Mostafa Modiri Delshad by Mostafa, Modiri Delshad

“…Backtracking search algorithm (BSA) as the new evolutionary technique of optimization is used for solving the problems. …”
Get full text
Get full text

Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…Researchers have in the past few decades resorted to several methods that are inspired from complex optimization problems. …”
Get full text
Get full text

Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

“…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
Get full text
Get full text
Get full text

Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

“…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
Get full text
Get full text

Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

“…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
Get full text
Get full text
Get full text
Get full text

A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems by Lutfy, Omar Farouq, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Abbas, Kassim A.

“…Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. …”
Get full text
Get full text
Get full text

Improving neural networks training using experiment design approach by Chong, Wei Kean

“…There are several methods of selecting training data from input space for neural networks which include D-optimal and Max-min design approaches. …”
Get full text
Get full text

A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization by Ee, L.K., Aziz, I.A.

“…Artificial Neural Networks (ANN) have been selected as the most suitable method to be adopted for such model. …”
Get full text
Get full text

A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization by Ee, L.K., Aziz, I.A.

“…Artificial Neural Networks (ANN) have been selected as the most suitable method to be adopted for such model. …”
Get full text
Get full text

INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM by MOHAMED ABDELGADIR, KHALID HAROUN

“…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
Get full text
Get full text

Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

“…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
Get full text
Get full text
Get full text
Get full text

An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
Get full text
Get full text
Get full text
Get full text

Reproducing kernel Hilbert space method for cox proportional hazard model by Abdul Manaf, Nur'azah

“…This algorithm is used to determine the vector i a that enables us to find the optimal parameters of ƒ(x)which is simplified as F(x)= ∑aᵢK(x,xᵢ) . …”
Get full text
Get full text
Get full text

A fuzzy case-based reasoning model for software requirements specifications quality assessment by Mostafa S.A., Gunasekaran S.S., Khaleefah S.H., Mustapha A., Jubair M.A., Hassan M.H.

“…Additionally, for efficient cases retrieval in the CBR, relevant cases selection and nearest cases selection heuristic search algorithms are used in the system. …”

A phonetically rich and balanced lexical corpus using zipfian distribution for an under resourced language / Aminath Farshana by Aminath , Farshana

“…The results show that the sentences selected using proposed method cover all the phonetic units and is 14 times smaller than the corpus developed using the benchmark method. …”
Get full text
Get full text
Get full text

Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection by Ghanem, Waheed Ali Hussein Mohammed

“…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
Get full text
Get full text

Optimal selection of location, sizing and power factor for solar PV plants using differential evolution by Dang Huy P., Ramachandaramurthy V.K., Pesaran H.A.M.