Search Results - (( java applications customization algorithm ) OR ( knowledge generation function algorithm ))
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Fuzzy Type-1 Triangular Membership Function Approximation Using Fuzzy C-Means
Published 2020“…Initially, the Fuzzy C-means algorithm is utilized to generate the parameters values of the Gaussian membership function. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
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Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm
Published 2013“…The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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Multiple case-based retrieval for university course timetabling problem
Published 2016“…This research summarize that the algorithm in retrieval is playing a very important role for an effective timetabling generator. …”
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Hybrid subjective evaluation of rule Exraction Algorithm using Weighted Subsethood-Based (WSBA)
Published 2013“…Fuzzy rules are important elements that being highlighted in any fuzzy expert system.This research proposes the framework of subjective performance evaluation using fuzzy technique for ranking the performance of the financial performance of a company under a multi criteria environment.There are a lot of techniques used such as fuzzy similarity function, fuzzy synthetic decision and satisfaction function have been adopted.The framework is based on fuzzy multi-criteria decision-making that consists of fuzzy rules.The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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Statistical analysis, ciphertext only attack, improvement of generic quasigroup string transformation and dynamic string transformation
Published 2018“…Quasigroup String transformation is one of those primitives that have many applications in cryptographic algorithms, Hash functions, and Pseudo-Random Number Generators. …”
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Biological-based semi-supervised clustering algorithm to improve gene function prediction
Published 2011“…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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The impact of population size on knowledge acquisition in genetic algorithms paradigm: Finding solutions in the game of Sudoku
Published 2010“…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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An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation
Published 2017“…Although useful, meta-heuristic algorithms that make up these strategies often require specific domain knowledge in order to allow effective tuning before good quality solutions can be obtained. …”
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Automated Model Generation Approach Using MATLAB
Published 2011“…Model generators can also be categorized into the black, grey or white box approaches, depending on the level of existing knowledge of the system’s structure and parameters. …”
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Discovering decision algorithm from a distance relay event report
Published 2009“…In helping the protection engineers deal with this overwhelming data, this study relied merely on digital protective relay’s recorded event report because, among other intelligent electronic devices, digital protective relay sufficiently provided virtually most attributes needed for data mining process in knowledge discovery in database. The method of discovering the distance relay decision algorithm essentially involved formulating rough set discernibility matrix and function from relay event report, finding reducts of pertinent attributes using genetic algorithm and finally generating relay prediction rules. …”
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Assessing the outcome of Competencies Level from Knowledge-Based Project
Published 2008“…This project is the new idea to implement the Knowledge Management by applying the concept of Knowledge Map and Social Network Map, which are the basic implementation of Knowledge Management, with Artificial Neural Network (ANN) Algorithm ofArtificial Intelligence System. …”
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Final Year Project -
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An Innovative Signal Detection Algorithm in Facilitating the Cognitive Radio Functionality for Wireless Regional Area Network Using Singular Value Decomposition
Published 2011“…This thesis introduces an innovative signal detector algorithm in facilitating the cognitive radio functionality for the new IEEE 802.22 Wireless Regional Area Networks (WRAN) standard. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…The clusters are generated from the clustering graphs. To evaluate the performance, BOCEDS algorithm is executed on two syntactic and one practical data streams. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…Total rules number, rules length and rules accuracy for the generation rules are recorded. The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Improving intrusion detection using genetic algorithm
Published 2013“…GA functions on a number of possible solutions using the principle of survival of the fittest with the aim to generate better approximations to solve a particular problem GA is facing. …”
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