Search Results - (( java application search algorithm ) OR ( knowledge generation using algorithm ))

Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Secondly, an expert system using Java programming technology with two tiers of search engine was developed to perform a fast selection of candidate materials in huge volume. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

“…This study aims to compare the performance of Boyer-Moore, Knuth morris pratt, and Horspool algorithms in searching for the meaning of words in the Java-Indonesian dictionary search application in terms of accuracy and processing time. …”
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An Effective Fast Searching Algorithm for Internet Crawling Usage by Chia, Zhen Hon, Nor Azhar, Ahmad

“…The search algorithm is a crucial part in any internet applications. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

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Songs Search Using Human Humming Voice by Abdul Rahman, Mohamad Ariff

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Message based random variable length key encryption algorithm. by Mirvaziri, Hamid, Jumari, Kasmiran, Ismail, Mahamod, Mohd Hanapi, Zurina

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An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

“…Initially, this tool adopts only Crow Search, Jaya, and Sine Cosine algorithms. But more metaheuristics will be included in future research. …”
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Evolutionary Music; Composing Beats and Chords Progression by Ng, Hayden

“…Evoluthm utilizes Harmony Search Algorithm and JFUGUE techniques in compliances with artificial intelligence (AI). …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Comparative study of apriori-variant algorithms by Mutalib, Sofianita, Abdul Subar, Ammar Azri, Abdul Rahman, Shuzlina, Mohamed, Azlinah

“…However, the algorithm suffers from scanning time problem while generating candidates of frequent itemsets.This study presents a comparative study between several Apriori-variant algorithms and examines their scanning time.We performed experiments using several sets of different transactional data.The result shows that the improved Apriori algorithm manage to produce itemsets faster than the original Apriori algorithm.…”
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Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot by Adriansyah, Andi, H. M. Amin, Shamsudin

“…The scheme is validated using parameters of MagellanPro mobile robot and tested by simulation using MATLAB/ SIMULINK. …”
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Hybrid genetic algorithm for improving fault localization by Mahamad Zakaria, Muhammad Luqman, Sharif, Khaironi Yatim, Abd Ghani, Abdul Azim, Koh, Tieng Wei, Zulzalil, Hazura

“…Therefore, there is a need for a technique which able to localize a fault effectively with less number of mutants generated. Genetic algorithm (GA) is well known in finding an optimal solution to a problem while local search is capable of removing duplication. …”
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An initial state of design and development of intelligent knowledge discovery system for stock exchange database by Che Mat @ Mohd Shukor, Zamzarina, Khokhar, Rashid Hafeez, Md Sap, Mohd Noor

“…We divide our problem in two modules.In first module we define Fuzzy Rule Base System to determined vague information in stock exchange databases.After normalizing massive amount of data we will apply our proposed approach, Mining Frequent Patterns with Neural Networks.Future prediction (e.g., political condition, corporation factors, macro economy factors, and psychological factors of investors) perform an important rule in Stock Exchange, so in our prediction model we will be able to predict results more precisely.In second module we will generate clustering algorithm. Generally our clustering algorithm consists of two steps including training and running steps.The training step is conducted for generating the neural network knowledge based on clustering.In running step, neural network knowledge based is used for supporting the Module in order to generate learned complete data, transformed data and interesting clusters that will help to generate interesting rules.…”
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Eye Diagram Modeling Of High-Speed Channels Using Artificial Neural Networks With An Improved Adaptive Sampling Algorithm by Goay, Chan Hong

“…The adaptive sampling technique is used for the data generation due to its flexibility where it generates samples according to the non-linearity of the regions in the design space. …”
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Development of mobile location based notification for crime cases tracking as an alternative alert for public safety / Noraini Ismail by Ismail, Noraini

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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…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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Comparison between Market Basket Analysis and Partition Around Medoids clustering for knowledge discovering in consumer consumption pattern / Mohammad Adha Ruslan, Nurul Shahira Mo... by Ruslan, Mohammad Adha, Mohammad Ramly, Nurul Shahira, Saberi, Nor Hasliza

“…The main purpose of this study are to compare the knowledge discovery between Market Basket Analysis and Partition Around Medoids and followed by to generate a customer buying pattern by using Market Basket Analysis (MBA) Algorithm and Partition Around Medoids (PAM) Clustering Algorithm. …”
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Test case minimization applying firefly algorithm by Hashim, Nor Laily, Dawood, Yasir Salman

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Discovering Pattern in Medical Audiology Data with FP-Growth Algorithm by G. Noma, Nasir, Mohd Khanapi, Abd Ghani

“…There is potential knowledge inherent in vast amounts of untapped and possibly valuable data generated by healthcare providers. …”
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Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm by Othman, Mahmod, Khalid, Shaiful Annuar, Abdullah, Fader, Amir Hamzah, Shezrin Hawani, Ku-Mahamud, Ku Ruhana

“…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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