Search Results - (( set generation method algorithm ) OR ( program implementation learning algorithm ))

Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

“…The classification accuracy, the number of rules and the maximum length of rules obtained from the SIPIDRIP method was compared with other rough set method such as Genetic Algorithm (GA), Johnson, Holte l R, Dynamic and Exhaustive method. …”
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Problem restructuring in interger programming for reduct searching by Ungku Chulan, Ungku Azmi Iskandar

“…Although this measurement is just an approximation, it can be proven to work. To implement the experiment, five data sets were taken. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…In the algorithm development a step-by-step example of the algorithm implementation is presented and then successfully implemented in Lego Mindstorm obstacle avoiding mobile robot as a proof of concept implementation of the hybrid AI algorithm. …”
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Virtual reality in algorithm programming course: practicality and implications for college students by Dewi, Ika Parma, Ambiyar, Mursyida, Lativa, Effendi, Hansi, Giatman, Muhammad, Efrizon, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

“…The analysis of learning problems shows the unavailability of interactive learning media that can support various learning styles of students in programming algorithm materials. …”
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SEALiP: A simple and efficient algorithm for listing permutation via starter set method by Ibrahim, Haslinda, Zake, Lugean, Omar, Zurni, Karim, Sharmila

“…Algorithm for listing permutations for n elements is an arduous task.This paper attempts to introduce a novel method for generating permutations.The fundamental concept for this method is to seek a starter set to begin with as an initial set to generate all distinct permutations. …”
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Comparison between starter sets generation method for listing all permutations by Karim, Sharmila, Ibrahim, Haslinda, Omar, Zurni

“…distinct permutations is an exhaustive process.Using starter set, the process of listing the permutations becomes easy.However a problem arises when the equivalence starter sets will generate the similar permutation and needed to be discarded.Two new recursive strategies are proposed to generate starter sets without generating equivalence starter sets namely circular and exchange two elements operation.Once the starter sets are obtained, the circular and reverse of circular operation are employed to produce distinct permutation from each starter sets.Computational advantages are presented comparing the results obtained by the new method with two other existing methods.The result indicates that the exchange two elements based strategy is faster than the circular based.Overall all new algorithms are better than existing algorithms in time execution.…”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

A permutation parallel algorithm under exchange restriction with message passing interface by Karim, Sharmila, Omar, Zurni, Ibrahim, Haslinda

“…The permutation generation method is based on starter sets generation under exchange operation and exploited it for listing down all n! …”
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A new domain specific scripting language for automated machine learning pipeline by Masrom, S., Rahman, A.S.A., Omar, N., Baharun, N.

“…However, in respond to the implementation difficulty, there exists a limited software tool that support easy implementation for automated machine learning based on Genetic Programming. …”
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Rapid software framework for the implementation of machine learning classification models by Rahman, A.S.A., Masrom, S., Rahman, R.A., Ibrahim, R.

“…However, to implement a complete machine learning model involves some technical hurdles such as the steep learning curve, the abundance of the programming skills, the complexities of hyper-parameters, and the lack of user friendly platform to be used for the implementation. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…The experiments were conducted on self generated data sets (7 different sets) and well known datasets (Mushroom & Cars Data set). …”
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A new starter sets generation method by fixing any element under exchange restriction by Karim, Sharmila, Ibrahim, Haslinda, Omar, Zurni, Sapiri, Hasimah

“…Permutation array are of recent interest because of their application to data transmission over power lines.A new permutation technique based on distinct starter sets by employing circular and reversing operations.The crucial task is to generate the distinct starter sets by eliminating the equivalence starter sets.Meanwhile a new strategy for starter sets generation without generating its equivalence starter sets were developed and more efficient in terms of computation time compared to old method. …”
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A new method for starter sets generation by fixing any element by Karim, Sharmila, Ibrahim, Haslinda, Sapiri, Hasimah

“…a new permutation technique based on distinct starter sets was introduced by employing circular and reversing operations.The crucial task is to generate the distinct starter sets by eliminating the equivalence starter sets.Meanwhile new strategies for starter sets generation without generating its equivalence starter sets were developed and more efficient in terms of computation time compared to old method.However all these algorithms have limitations in terms of fixing element to construct the first set (starter set) to begin with.It would be interesting to derive new strategy by fixing an element in any position. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem by Ismail, Zuhaimy, Nurhadi, Irhamah, Zainuddin, Zaitul Marlizawati

“…Genetic Algorithm as population-based methods are better identifying promising areas in the search space, while Tabu Search and Simulated Annealing as trajectory methods are better in exploring promising areas in search space. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…Also, the proposed models for learning in data sets generated the classification rules faster than other methods. …”
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New recursive circular algorithm for listing all permutations by Karim, Sharmila, Omar, Zurni, Ibrahim, Haslinda, Othman, Khairil Iskandar, Suleiman, Mohamed

“…In this paper, a new recursive strategy is proposed to generate starter sets that will not incur equivalence by circular operation. …”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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Parallel strategy for starter sets to list all permutation based on cycling restriction by Karim, Sharmila, Omar, Zurni, Ibrahim, Haslinda, Othman, Khairil Iskandar

“…This paper presents a parallel implementation of a new permutation generation method.This permutation generation method is based on the starter sets for listing all the n! …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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