Search Results - (( developing effective predictor algorithm ) OR ( java application path algorithm ))
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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Visdom: Smart guide robot for visually impaired people
Published 2025“…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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REDUCING LATENCY IN A VIRTUAL REALITY-BASED TRAINING APPLICATION
Published 2006“…In order to overcome latency problem, this research is an attempt to suggest a new prediction algorithm based on heuristic that could be used to develop a more effective and general system for virtual training applications. …”
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Application of Krylov Subspace methods for solving Continuous Power Flow problem in voltage stability analysis of power system
Published 2010“…These developed algorithms are tested on 14, 118 and 300 IEEE bus systems. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Using hill climbing from search and score algorithms, the Bayesian network analysis revealed that there were associations among the network covariates, while cofounding effects of SES were observed. …”
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Dynamic intrusion detection method for mobile ad hoc network using CPDOD algorithm
Published 2010“…In this paper, we propose a novel intrusion detection method by combining two anomaly methods Conformal Predictor k-nearest neighbor and Distancebased Outlier Detection (CPDOD) algorithm. …”
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Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables
Published 2025“…Effective prediction of Aedes mosquito abundance and dengue risk indicators such as the Aedes Index (AI) and Dengue Positive Trap Index (DPTI) is essential for early intervention and targeted vector control. …”
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Modeling of CO emissions from traffic vehicles using artificial neural networks
Published 2019“…The model was developed using six traffic CO predictors: number of vehicles, number of heavy vehicles, number of motorbikes, temperature, wind speed and a digital surface model. …”
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Development of genetic algorithm for optimization of yield models in oil palm production
Published 2018“…Nonetheless, the advance in computer technology has created a new opportunity for the study of modelling as selecting variables intended to choose the “best” subset of predictors. Owing to this great interest in the predictions, the study aims to develop a genetic algorithm (GA) to identify the relevant variables and search for the best combinations for modelling to examine the potential of oil palm production in Sarawak and Sabah, Borneo, Malaysia, under a given set of assumptions. …”
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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“…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. …”
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Finding an effective classification technique to develop a software team composition model
Published 2018“…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. …”
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Moderating effect of management support on the relationship between HR practices and employee performance in Nigeria
Published 2019“…The overall findings signify that recruitment and selection, training and development, performance appraisal and succession planning are strong and positive predictors of employee performance, and management support is a moderator in training and development–employee performance relationship, and in compensation–employee performance connection. …”
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Comparing three methods of handling multicollinearity using simulation approach
Published 2006“…The goal was to develop a linear equation that relates all the predictor variables to a response variable. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…However, it cannot be applied when the sample size is less than the number of predictor variables. In addressing this problem, some robust procedures for high dimensional dataset via the RFCH algorithm are developed. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…In this study, the RVM model was employed to determine a predictive association between predictand variables and predictors.…”
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A Comparative Study On Some Methods For Handling Multicollinearity Problems
Published 2006“…The goal was to develop a linear equation that relates all the predictor variables to a response variable. …”
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A comparative study on some methods for handling multicollinearity problems
Published 2006“…The goal was to develop a linear equation that relates all the predictor variables to a response variable. …”
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