Search Results - (( developing models (matching OR machine) algorithm ) OR ( java application testing algorithm ))

Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…On the Construction phase, the development of the prototype has been started. All the algorithm for the engine has been developed by using Java script language. …”
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Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

“…Ultimately, the algorithm development program designed earlier is linked up directly to the robotic model for program implementation and verification. …”
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Multi-sources model and control algorithm of an energy management system by Hannan, MA, Azidin, FA, Mohamed, Azah

“…This paper presents the multi-sources energy models and ruled based feedback control algorithm of an energy management system (EMS) for light electric vehicle (LEV), i.e., scooters. …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

“…The BBO-VNS match-up algorithm manipulates the idle times on machines within the time horizon for assigning the affected operations by breakdown and/or newly arrived orders. …”
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Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

“…Successful reservoir interpretation mostly depends on the precision of the history matching. History matching is an act of adjusting the developed model in simulating the past reservoir performance to match the actual historical data. …”
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The development of integrated planning and scheduling framework for dynamic and reactive environment of complex manufacturing problem by Zakaria, Zalmiyah, Deris, Safaai, Mat Yatim, Safie, Othman, Muhamad Razib

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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

“…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform by Abdul Rashid, Abdul Hadi

“…Then the proposed algorithm for DCT and GA can be applied to the history matching problem. …”
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Risk perception modeling based on physiological and emotional responses / Ding Huizhe by Ding , Huizhe

“…This research aims to develop models for objectively assessing perceived risk. …”
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LINGUISTIC FUZZY MODELING IN LASER MACHINING QUALITY EVALUATION by Sivarao, Subramonian

“…The finding shows that, the developed lingual fuzzy model has produced a sound output as it matches closely and agrees well to the experimental result.…”
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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Artificial neural network and inverse solution method for assisted history matching of a reservoir model by Negash, B.M., Vel, A., Elraies, K.A.

“…This allows to directly simulate the trained neural network and avoid the use of objective function and optimization algorithm. The efficacy of the developed approach was evaluated using a benchmark reservoir model case study which was originally developed for investigation of three-phase three-dimensional Black-Oil modelling techniques under the 9th SPE comparative study project. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…An extreme learning machine, the multi-kernel least square support vector machine model (MKLSSVM), is developed to predict the water level of a reservoir in Malaysia. …”

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

“…In addition, one of the main challenges has been development of efficient algorithm for solving aforementioned model to find exact feasible optimal solution. …”
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Deep learning model for predicting and detecting overlapping symptoms of cardiovascular diseases in hospitals of UAE by Abbas Alhadeethy, Najwa Fadhil, Khedher, Akram M Z M, Shah, Asadullah

“…DL strengths comprises of its potential to automatically diagnose clinical appearances, enhance decision-making, recognizing the phenotypes, and effectively select treatment methodology to complex diseases. The DL algorithm that can be well matched to chemistry is the hemodynamic and electrophysiological parameters catalogues that are effectively captured over continuous periods by wearable machines, as well as the division of images into captured images or pictures (Nagueh, 2016). …”
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Predicting Cheaters in PlayerUnknown’s Battlegrounds (PUBG) using Random Forest Algorithm by Nurin Alya, Haris

“…This study aims to address this issue by developing a reliable prediction model to identify potential cheaters in PUBG matches. …”
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Octane number prediction for gasoline blends using convolution neural network / Zhu Yue by Zhu , Yue

“…At present, there are many prediction algorithms based on machine learning. According to the "80/20 rule" for building machine learning model, 80% of the time is spent of finding, cleaning, and organizing data, while the remaining 20% for training of the machine learning model. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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