Search Results - (( using simulation a algorithm ) OR ( basic selection method algorithm ))

VHDL modeling of optimum measurement selection by using genetic algorithm by Ullah, Mohammad Habib, Hasan, Muhammad Asfarul, Uddin, Md. Jasim, Priantoro, Akhmad Unggul

“…A Genetic Algorithm (GA) that is going to be a part of a system for obtaining optimum sensor measurements for a specific process. …”
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Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches by Mohd Pauzi, Nur Fazlinda

“…Artificial Bee Colony (ABC) algorithm is one of the methods used to solve the flowshop scheduling problem but only a few researches have been found using this method in this area. …”
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Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours by Baneamoon, Saeed Mohammed Saeed

“…The simulated robot is also tested on many examples of a complex behaviour which is any combination of the four basic behaviours and the results have shown that it performs better with this type of behaviours as well.…”
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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.

The advantages of genetic algorithm and neural networks to forecast air pollution trend in Malaysia: an overview / Mohamad Idham Md Razak … [et al.] by Md Razak, Mohamad Idham, Ahmad, Ismail, Bujang, Imbarine, Talib, Adi Hakim, Kedin, Nor Adila

“…Genetic Algorithms (GAs) are adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. …”
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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. …”
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FPGA implementation of the complex division in digital predistortion linearizer by Mohammady, Somayeh, Varahram, Pooria, Mohd Sidek, Roslina, Hamidon, Mohd Nizar, Sulaiman, Nasri

“…It all depends on the requirements, such as accuracy, size and speed. A few suitable algorithms should be selected and implemented in VHDL for evaluation. …”
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Effect of model simplification through manual reduction in number of surfaces on room acoustics simulation by Abd Jalil, Nurul Amira, Che Din, Nazli, Keumala, Nila, Abdul-Razak, Asrul Sani

“…Model simplification is an important step in room modelling for acoustics simulation. Various simplification algorithms were previously suggested. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…Good performances were also achieved with the NPO with respect to noise and limited information problems. A Wilcoxon Signed-Rank Test was performed to measure the pair-wise statistical performances of the algorithms and from the results, NPO recorded a better statistical performance compared to the other benchmarking algorithms. …”
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Statistical modeling of the electromechanical behaviour of BI-2223 composite wires by Muhammad Faris Fuaad

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) . …”
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Vision Based Calibration and Localization Technique for Video Sensor Networks by Mohamed Sharif, Sharif Amar Mohamed Sharif

“…The literature is replete with many localization and calibration algorithms that basically rely on some a-priori chosen nodes, called seeds, with known coordinates to help determine the network topology. …”
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Earth observation micro-satellite design optimization using satellite simulator / Robertus Heru Triharjanto … [et al.] by Heru Triharjanto, Robertus

“…It is also find that due to full acces level, the self-made simulator as used in the research has good potential to be used in the optimization case with search algorithm.…”
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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). …”
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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.…”
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Optimal planning and design of hybrid renewable energy system for rural healthcare facilities / Olatomiwa Lanre Joseph by Olatomiwa Lanre , Joseph

“…Followed by development of prediction algorithm for solar radiation using soft-computing methodologies. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

“…These methods are M1 and M2, and they basically differ in the type of input-output data used to train the artificial neural network. …”
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Deterministic phase sequence approach for peak to average power ratio reduction in orthogonal frequency division multiplexing systems by Kazemian, Mohsen

“…The proposed idea reduces the computational complexity, processing time and the side information matrix content, basically and ensures the results. The first proposed method, called Gray Code-based Phase sequence (GCP) is a new low complexity PAPR reduction scheme based on a Gray code structure and a similarity measurement block; included on two steps: firstly, selecting the phase sequences based on Gray codes and finally, evaluating the similarity between the input and the output of the Power Amplifier (PA), among the selected phase sequences in the previous step. …”
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A hybrid particle swarm optimization approach and its application to solving portfolio selection problems by Shamshul Bahar, Yaakob, Prof. Madya, Watada, Junzo

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

“…In addition, it improves classification metrics in comparison to basic feature selection methods.…”
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