Search Results - (( developing scale prediction algorithm ) OR ( java loading optimization algorithm ))
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Monograph -
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids
Published 2023“…Our results have strong implications for SDM development, revealing the inconsistencies introduced by the choice of algorithm on scale optimisation, with GLM selecting broader scales than RF.…”
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Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Monograph -
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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6
Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables
Published 2025“…However, current models often rely on coarse regional data and fail to account for microclimatic variations, limiting their predictive accuracy in dengue hotspots. This study developed fine-scale predictive models using machine learning algorithms; Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machines (SVM) to estimate mosquito abundance and dengue risk at the species level based on daily microclimatic data (temperature, relative humidity, and rainfall) collected over 26 weeks in Kuala Selangor, Malaysia. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower
Published 2018“…The verification results indicate that all the structural defects were predicted with high accuracy by the developed hybrid algorithm in cases of healthy and damaged structures. …”
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Artificial neural network model for predicting windstorm intensity and the potential damages / Mohd Fatruz Bachok
Published 2019“…Local conditions wind multiplier map, hazard threshold, and damage scales are three supporting tools that were developed to compliment the predictive model. …”
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10
Performance Measurement on Deep Spiking Neural Network (DSNN) Algorithm in Flood Prediction Environment
Published 2023“…There are several algorithms used to predict floods, including LSTM, BP, MLP, SARIMA, and SVM. …”
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Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network
Published 2021“…Prior to the development of ANN-based WQI prediction model, the BR algorithm was chosen with two-, three-, four-, five- and six-neuron architectures for 60% and 70% training. …”
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Monograph -
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An Optimized ANN Measure-Correlate-Predict Method for Long-term Wind Prediction in Malaysia
Published 2023Conference Paper -
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Can the future really be predicted?
Published 2013“…Therefore, it is computationally infeasible to develop full-scale models with the present computing technology. …”
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Proceeding Paper -
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Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms
Published 2011“…The next objective of the current study was to compare the performance of aforementioned algorithms with regard to predicting ability. The investigation of TEA-based esterquat cationic surfactant synthesis was started in a 50 ml scale. …”
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Intelligent technique for grading tropical fruit using magnetic resonance imaging
Published 2013“…Our purpose, in this study, is to develop a non-destructive method to predict the status of orange fruits, based on internal quality. …”
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Hybrid DE-PEM algorithm for identification of UAV helicopter
Published 2014“…Purpose – The purpose of this paper is to develop a hybrid algorithm using differential evolution (DE) and prediction error modeling (PEM) for identification of small-scale autonomous helicopter state-space model. …”
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Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman
Published 2024“…A prototype architecture and a user-friendly graphical interface tailored for SVM-based outbreak predictions are developed, accompanied by detailed code snippets elucidating essential steps in data loading, encoding, scaling, and SVM model training. …”
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Parallel Implementation of Two Level Barotropic Models Applied to the Weather Prediction Problem
Published 2004“…To process the data collected from British Atmospheric Data Centre (BADC), the sequential programs in row and columnwise fashions are developed and implemented. Then the parallel algorithms are constructed and run using the Beowulf Cluster machine. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…This thesis proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. The research is divided into three parts, which are (1) dataset development, (2) algorithm development, and (3) algorithm performance evaluation. …”
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