Search Results - (( _ normalization techniques algorithm ) OR ( java evaluation method algorithm ))
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Improved normalization and standardization techniques for higher purity in K-means clustering
Published 2016“…Clustering is an unsupervised classification method with aim of partitioning, where objects in the same cluster are similar, and objects belong to different clusters vary significantly, with respect to their attributes. The K-means algorithm is a famous and fast technique in non-hierarchical cluster algorithms. …”
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2
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
3
JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation
Published 2008“…It is also shown that this technique is fully format compliance as most of other techniques do. …”
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4
Security Analysis Between Static And Dynamic S-boxes In Block Ciphers
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Article -
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An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms
Published 2015“…It is concluded that the resultant hybrid techniques can perform well if the variables provided to normalization by neighborhood model (MF and CF) do not have big differences in order for the hybrid normalization model to outperform every algorithm in comparison.…”
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Thesis -
6
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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7
An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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8
Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…To help engineers select the best metaheuristic algorithms for their problems, there is a need to evaluate the performance of different metaheuristic algorithms against each other using common case studies. …”
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Conference or Workshop Item -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…An experimental analysis is conducted by several experiments to evaluate the performance of the proposed ensemble methods which has been tested on the 4 benchmark datasets, namely LingSpam, SpamAssassin, Spambase and CSDMC2010. …”
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10
Text normalization algorithm for facebook chats in Hausa language
Published 2014“…It was found that our proposed algorithm was able to normalized Hausa NSWs with an accuracy of 100%. …”
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Proceeding Paper -
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Conference or Workshop Item -
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The Impact of Normalization Techniques on Performance Backpropagation Networks
Published 2004“…This study explored several normalization techniques using backpropagation learning. …”
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Thesis -
13
Design and analysis of sequence generator module using eulerian path algorithm for DNA fragment assembly / Mustaqim Mohd Subri
Published 2013“…This project is to design and analysis the sequence generator module using Eulerian Path algorithm for DNA fragment assembly. Traditionally, “overlap-layoutconsensus” technique is used for DNA fragment assembly, but this technique has a problem in assembling a long sequence of DNA which a new technique needs to be used to overcome this problem. …”
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Student Project -
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A multi-filter feature selection in detecting distributed denial-of-service attack
Published 2019“…In addition, the proposed M2FS method is developed through WEKA API with Java Programming language using the IDE of Eclipse Java. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
Conference paper -
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…Another possibility is to apply a bootstrap technique which does not rely on the normality assumption. …”
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Thesis -
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The software metric thresholds were used as indication for identifying unsafe design in software engineering. To evaluate this technique, an experiment was conducted on two geospatial systems developed using Java programming language where the Chidamber and Kemerer (CK) metrics were used. …”
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Thesis -
20
Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024“…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. …”
Conference Paper
