Search Results - (( java application drops algorithm ) OR ( parameter classification rules algorithm ))
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…Fuzzy modeling is a process of generating parameters which are fuzzy rule and membership function. …”
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Undergraduates Project Papers -
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Adaptive parameter control strategy for ant-miner classification algorithm
Published 2020“…A key aspect of this algorithm is the selection of an appropriate number of terms to be included in the classification rule. …”
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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength
Published 2015“…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The third stage is to classify individual jammers according to the specific pattern and characteristics design as defined in jamming identification and classification parameters. It involves development of Max-Min Rule-Based Classification Algorithm. …”
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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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Conference or Workshop Item -
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation
Published 2023Article -
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Predicting heart disease using ant colony optimization / Siti Aisyah Ismail
Published 2021“…Thus, this study used the Ant Colony Optimization algorithm with data mining called Ant-Miner to predict heart disease because it is said that Ant-Miner’s rule list is simpler than other rule induction algorithms. …”
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Student Project -
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Modified anfis architecture with less computational complexities for classification problems
Published 2018“…Even though it has been widely used, ANFIS architecture still has a drawback of computational complexities. The number of rules and its tunable parameters increase exponentially which created the problem of curse of dimensionality. …”
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Power quality problem classification based on Wavelet Transform and a Rule-Based method
Published 2010“…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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Conference or Workshop Item -
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Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method
Published 2010“…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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Conference or Workshop Item -
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Power Quality Problem Classification Based on Wavelet Transform and a Rule-Based method
Published 2010“…This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. …”
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Conference or Workshop Item -
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…These results indicated that the proposed models with optimized hyper-parameters produced the accurate classification results. …”
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A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…A modified apriori algorithm was employed to reduce the number of clusters effectively on the basis of common data in the clusters of every input to obtain a minimal set of decision rules based on datasets. …”
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Improved personalised data modelling using parameter independent fuzzy weighted k-nearest neighbour for spatio/spectro-temporal data
Published 2021“…Upon exploration of the architecture, the weighted k-nearest neighbours algorithm used for the classification module is found to be prone to misclassification as it relies solely on the majority voting rule to determine the class for new data vector. …”
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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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