Search Results - (( java implication based algorithm ) OR ( knowledge acquisition testing algorithm ))

The impact of population size on knowledge acquisition in genetic algorithms paradigm: Finding solutions in the game of Sudoku by Abu Bakar, Nordin, Mahadzir, Muhammad Fadhil

“…Population size is an important component in genetic algorithms (GAs).The concept of population in GAs has contributed to a unique searching strategy which empower its search process through the massive volume of the data in a population.The purpose of this study is to see how the impact of population size on genetic algorithms in producing correct solution for a Sudoku puzzle.Sudoku is a Japanese number puzzle game that has become a worldwide phenomenon.The puzzle involves completing a grid of cells by assigning a single number to each cell.The numbers in a row or a column must consist of any one of the numbers from 1 to 9; no repetition is allowed.GA will be used to generate the correct solution of Sudoku puzzles.The mechanism to produce legal Sudoku grid will follow the requirements needed and meet all the constraints.A fitness function is designed to evaluate legal grids and GA will be tested for performance and time efficiency.The challenges lie on how GA will represent a Sudoku grid in the process and the effectiveness of its operators such as crossover and mutation.The results show how different population size can produce different solutions.The best performance is observed at 500 population size.The paper will conclude with an insight of this value and its significance to the knowledge acquisition in GA paradigm..…”
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Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

“…Consequently; this paper concludes that MALESAbrain is a new methodology for meeting, which (1) reduces the unnecessary human intervention and (2) changes a meeting atmosphere from debate to problem-based learning for the knowledge acquisition.…”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

“…A dataset of successful and unsuccessful applicants was taken and processed as training data and testing data used in the modelling process. Five algorithms were employed to develop a classification model in determining the award of the scholarship, namely J48, SVM, NB, ANN and RT algorithms. …”
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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

“…There are problem assessment, data acquisition, cropping, pre-processing, design, training, testing and documentation. …”
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Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq by Zebel , Al Tareq

“…The problem-based and the game-based programming workshops utilizing our problem-solving model using sorting algorithms were the experimental groups. A one-way ANOVA test indicated that the mean score for syntax-based workshop post test scores (M=6.99, SD=1.92) was significantly different than the post test scores of activity-based workshop (M=8.05, SD=1.96) and the post test scores of game-based workshop (M=8.62, SD=1.90). …”
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Arcing Faults Detection in Switchgear with Extreme Learning Machine by Ishak S., Koh S.P., Tan J.D., Tiong S.K., Chen C.P., Yaw C.T.

Implementation of case-based reasoning in help desk system by Tee, Shih Min

“…This is because CBR assists in reducing the effort and time required for knowledge acquisition and representation significantly.…”
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Improved prediction of daily pan evaporation using Bayesian Model Averaging and optimized Kernel Extreme Machine models in different climates by Ehteram M., Graf R., Ahmed A.N., El-Shafie A.

“…Bayesian networks; Climate models; Forecasting; Knowledge acquisition; Machine learning; Particle swarm optimization (PSO); Uncertainty analysis; Water resources; Wind; Bayesian model averaging; Daily pan evaporation; Gamma test; Kernel extreme learning machine model; Learning machines; Machine modelling; Optimization algorithms; Uncertainty; Water planning; Water resources management; Evaporation; algorithm; Bayesian analysis; evaporation; machine learning; numerical model; optimization; stochasticity; uncertainty analysis…”

An ontology-based reasoning framework for reaction mechanisms simulation by Alicia Tang, Y., Zain, S., Abdul Rahman, N., Abdullah, R.

“…The construction of these models is automated based on a set of QR algorithms. We have tested the framework on the S N 1 and the S N 2 reaction mechanisms. …”
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Investigations On Human Perceptual Maps Using A Stereo-Vision Mobile Robot by Eng, Swee Kheng

“…Spatial cognition is a branch of cognitive psychology concerning the acquisition, organization, utilization, and revision of knowledge about spatial environments. …”
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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.

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Determination of suitable resource discovery tool and methodology for high-volume internet of things (IoT) by Jamal, A.A., Bakar, M.T.A.

“…This paper discusses several issues supporting a knowledge-based methodology for discovery of high volume IoT resources in the simulator NS-3 environment. …”
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BLAZEBREAKER: GAMIFY THE FLAMES by SAID MOHD NAJIB, ELIAS

“…The practical implementation of the VR simulation involved in-depth research from fire safety experts and real-world testing to validate its effectiveness. The report concludes with an analysis of the results, highlighting the positive outcomes observed in user engagement, knowledge acquisition, and skill retention. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

“…The IncFRNN algorithm is able to control the size of training pool using predefined window size threshold. …”
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Enhancement of neural network based multi agent system for classification and regression in energy system by Yaw C.T., Yap K.S., Wong S.Y., Yap H.J., Paw J.K.S.