Search Results - (( java implementation bees algorithm ) OR ( using complex machine algorithm ))

Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar A., Kanthasamy R., Sait H.H., Zwawi M., Algarni M., Ayodele B.V., Cheng C.K., Wei L.J.

The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

“…Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”

Optimization of multi-holes drilling toolpath using tiki-taka algorithm by Norazlina, Abdul Rahman

“…The study aims to model the MDMT toolpath using the Traveling Salesman Problem (TSP) concept, apply TTA to optimize this model, and validate the model and algorithm through machining experiments on this problem. …”
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Propose a New Machine Learning Algorithm based on Cancer Diagnosis by Ali, Mohammed Hasan, Kohbalan, Moorthy, Anad, Mohammed Morad, Mohammed, Mohammed Abdulameer

“…Moreover, there are different reasons for using these algorithms such as the ability of machine learning to detect main features from complex data sets, which represents techniques have been utilized as an aim to model the progression and treatment of cancerous conditions. …”
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Power Consumption Optimization in CNC Turning Process Using Multi Objective Genetic Algorithm by Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Riza, Muhammad, Suprianto, Mohamad Yuhan

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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

Fuzzy Rules Optimization in Fuzzy Expert System for Machinability Data Selection: Genetic Algorithms Approach by Wong, Shaw Voon, Salem Hamouda, Abdel Magid

“…Machinability data selection is complex and cannot be easily formulated by any mathematical model to meet design specification. …”
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Optimization of Machining Parameters in Turning Operation Using PSO and AIS Algorithms: A Survey by Abbas, Adnan Jameel, Minhat, Mohamad, Abd Rahman, Md Nizam

“…Most papers in the field of turning parameters optimization are based on (PSO) algorithms, but only a few efforts that are using (AIS) algorithms. …”
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To study the multi-objective optimization of EDM using genetic algorithm by Fairuz, Idris

“…In the manufacturing industry, the production and quality of a product is very important, especially when it involves the big industries EDM. A machine such as EDM (electro discharge machine) used to produce a product that require an accurate product quality. …”
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Prediction of Ground Surface Deformation Induced by Earthquake on Urban Area Using Machine Learning by Usman F., Nanda, Sumantyo J.T.S.

“…Overall, the four machine learning algorithms have outstanding performance, with a coefficient determinant of more than 0.9. …”

An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus by Abu Bakar, Nordin, Abdul Kudus, Rosnawati

“…Learning is a complex cognitive process; thus, the algorithms that can simulate learning are also complex. …”
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Automated visual surveillance using kernel tricks by Ahmed, Tarem, Wei, Xianglin, Ahmed, Supriyo, Pathan, Al-Sakib Khan

“…We present three algorithms built using kernel machines to perform automated, real-time intruder detection in surveillance systems. …”
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Interpretation of machine learning model using medical record visual analytics by Mohd Khalid, Nur Hidayah, Ismail, Amelia Ritahani, Abdul Aziz, Normaziah

“…This paper analyzed several visual analytics approaches instantiated in machine learning algorithm for medical record analytics. …”
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Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

“…These machine learning algorithms develop a detection model in a training phase. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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Hybrid Algorithm for Hand Gesture Recognition by Gupta, Shikha, Jaafar, J., Wan Ahmad, Wan Fatimah

“…For the classification purpose Support vector machine has been used as a classifier.…”
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EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

“…Thus, this project proposed an optimised machine learning algorithms to classify emotion by analysing brain activity using Electroencephalogram (EEG) signals. …”
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Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

“…The mathematical equation become more complexes and it will be difficult to solve using manual calculation without any optimization technique or algorithm in this project. …”
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Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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