Search Results - (( rule extraction factor algorithm ) OR ( java application optimisation algorithm ))
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1
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Framework development in extracting rules from trained neural network / Shuzlina Abdul Rahman, Azlinah Hj Mohamed and Marina Yusoff
Published 2006“…In addressing this framework, the criteria of each approaches has been explored and analyzed from eight factors: process extraction, merit, demerit, rule type, type of data, rule quality, processing complexity, and the description of each RE technique. …”
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Research Reports -
3
Analysis of Traffic Accident Patterns Using Association Rule Mining
Published 2024“…This study also demonstrated the practicality of the apriori algorithm in analyzing extensive datasets to extract actionable insights. …”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase
Published 2004“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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Classification of stock market index based on predictive fuzzy decision tree
Published 2005“…In fuzzy reasoning method the weights are assigned to each proposition in the antecedent part and the Certainty Factor (CF) is computed for the consequent part of each Fuzzy Production Rule (FPR). …”
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis
Published 2016“…The domain expert has verified that the generated rules are able to explain the contributing factors towards failure analysis. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Simultaneously, news sentiment analysis techniques were used to discover the polarity of news according to each factor. From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Book Section -
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Refinement of generated weighted fuzzy production rules by using fuzzy neural networks for stock market prediction.
Published 2005“…The reasons for having these problems are 1) the WFPRs generated are not powerful enough to represent the domain knowledge, 2) the techniques used to generate WFPRs are pre- matured, ad-hoc or may not be suitable for the prediction problem, and 3) further refinement of the extracted rules has not been done. In this paper, we look into the solutions of the above problems by 1) enhancing the representation power of WFPRs by including local and global weights, 2) developing a fuzzy neural network (FNN) with enhanced learning algorithm, and 3) using this FNN to refine the local and global weights of WFPRs for stock market prediction. …”
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Integration of dual intelligent algorithms in shunt active power filter
Published 2013“…This paper presents an integration of dual intelligent algorithms: artificial neural network (ANN) based fundamental component extraction algorithm and fuzzy logic based DC-link voltage self-charging algorithm (fuzzy self-charging algorithm), in a three-phase three-wire shunt active power filter (SAPF). …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators
Published 2024“…Therefore, in this paper, a belief rule base (BRB) artificial intelligence inference algorithm based on GA optimization to determine the factors affecting customer churn for operators proposed. …”
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Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm
Published 2023“…In reducing the learning complexity, a genetic algorithm was implemented to optimize the logical rule throughout the learning phase in performing a 2-satisfiability-based reverse analysis method, implemented during the learning phase as this method was compared. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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14
Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013“…The experiment with 50% of data training and 50% of data testing in percentage split produced higher accuracy where the percentage of correctly classified instance was 76.2557%. The rules were extracted from the model and after the analyses were conducted the result showed that the domain factors of student performance were class attendance and the performance of the previous semester.…”
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Pattern extraction for programming performance evaluation using directed apriori
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Design, Modelling And Control Of Hybrid Energy Storage System For Electric Vehicles
Published 2021“…The proposed energy management strategy of HESS includes three control layers. The standard rule-based controller, the optimal adaptive rule-based controller, and the fuzzy adaptive rule-based controller were proposed to manage the energy flow of the HESS. …”
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Engine fault diagnosis using probabilistic neural network
Published 2021“…A benchmarked engine fault model is developed and simulated in Maltab. The proposed algorithm is designed to detect 9 common engine faults based on the information extracted from exhaust gas, such as hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx), carbon dioxide (CO2) and dioxygen (O2). …”
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Proceedings -
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Improving named entity recognition accuracy of gene and protein in biomedical text
Published 2011“…The plethora of biomedical material on the WWW is one of the factors that have sustained interest in automatic methods for extracting information from biomedical document, which can help biologists in their research. …”
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Finding an effective classification technique to develop a software team composition model
Published 2017“…Ineffective software team composition has become recognized as a prominent aspect of software project failures.Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection.It is also believed that the technique/s used while developing a model can impact the overall results.Thus, this study aims to: 1) discover an effective classification technique to solve the problem, and 2) develop a model for composition of the software development team.The model developed was composed of three predictors: team role, personality types, and gender variables; it also contained one outcome: team performance variable.The techniques used for model development were logistic regression, decision tree, and Rough Sets Theory (RST).Higher prediction accuracy and reduced patte rn complexity were the two parameters forselecting the effective technique.Based on the results, the Johnson Algorithm (JA) of RST appeared to be an effective technique for a team composition model.The study has proposed a set of 24 decision rules for finding effective team members.These rules involve gender classification to highlight the appropriate personality profile for software developers.In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models.…”
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Finding an effective classification technique to develop a software team composition model
Published 2018“…The study has proposed a set of 24 decision rules for finding effective team members. These rules involve gender classification to highlight the appropriate personality profile for software developers. …”
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