Search Results - (( developing local data algorithm ) OR ( java application learning algorithm ))
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Thesis -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Numerical Integration And Data Reduction For Application In Photometry
Published 2003“…In this thesis, an algorithm based on a local interpolation scheme called the Average Angle Method was developed for numerical integration and data reduction of photometric data, and in general, for any data set sharing similar characteristics as the luminous intensity data The new interpolation scheme interpolates discrete data with piecewise cubic polynomials having a CI continuity in the interior. knots. …”
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Semi-automatic oil palm tree counting from pleiades satellite imagery and airborne LiDAR / Nurul Syafiqah Khalid
Published 2020“…This study aimed to develop the automatic oil palm tree counting using remote sensed data and two different algorithms at Felda Pasoh. …”
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Data clustering using the bees algorithm
Published 2007“…The main problem with this clustering method is its tendency to converge to local optima. The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin
Published 2024“…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…This study developed an optimized variation of the DV-Hop localization algorithm for anisotropic wireless sensor networks. …”
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Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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Chaotic Mapping Lion Optimization Algorithm-Based Node Localization Approach for Wireless Sensor Networks
Published 2023“…Therefore, this paper develops a Chaotic Mapping Lion Optimization Algorithm-based Node Localization Approach (CMLOA-NLA) for WSNs. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Design and analysis of management platform based on financial big data
Published 2023“…Traditional financial accounting will become limited by new technologies which are unable to meet the market development. In order to make financial big data generate business value and improve the information application level of financial management, aiming at the high error rate of current financial data classification system, this article adopts the fuzzy clustering algorithm to classify financial data automatically, and adopts the local outlier factor algorithm with neighborhood relation (NLOF) to detect abnormal data. …”
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Metaheuristic optimization techniques for localization in outdoor wireless sensor networks: a comprehensive review
Published 2025“…This paper serves as a comprehensive background on localization algorithms and methods used in wireless sensor networks, offering insights for researchers to develop efficient localization algorithms tailored to specific application requirements in diverse work environments.…”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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An Evaluation of Machine Learning Algorithms for Missing Values Imputation
Published 2019“…It represents the research and imputation of missing values in gene expression data. By using the local or global correlation of the data we focus mostly on the contrast of the algorithms. …”
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Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Improvement DACS3 Searching Performance using Local Search
Published 2009“…Several versions of metaheuristic ACOs’ have been developed through several improvement processes to produce better algorithm. …”
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Missing-values imputation algorithms for microarray gene expression data
Published 2019“…The aim was to adapt the algorithms to the characteristics of the data.…”
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