Search Results - (( java implementation max algorithm ) OR ( framework implementation developing algorithm ))
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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Batch mode heuristic approaches for efficient task scheduling in grid computing system
Published 2016“…Many algorithms have been implemented to solve the grid scheduling problem. …”
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Quantum Processing Framework And Hybrid Algorithms For Routing Problems
Published 2010“…The framework is used to increase the implementation performance of quantum algorithms. …”
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…The scripting language is designed and developed based on the algorithm structure that is defined in the proposed implementation frameworks with the dynamic parameterization. …”
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Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment
Published 2011“…The first algorithm, named as Framework Initialization algorithm, is developed to initialize the framework and discovering the subsystems configured in order to derive the interoperation tasks. …”
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Implementing case-based reasoning approach to framework documentation
Published 2023“…This paper discusses and implements the case-based reasoning (CBR) approach to documenting a framework. …”
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Development of a task-oriented, auction-based task allocation framework for a heterogeneous multirobot system
Published 2020“…The developed framework consists of a novel heuristic-based task allocation algorithm and communication module. …”
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…This thesis presents investigations into the development of an intelligent framework for modelling and active vibration control (AVC) of flexible structures. …”
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Genetic algorithm based ensemble framework for sentiment analysis
Published 2018“…Finally, the last experiment involves creating the complete optimized multilayered ensemble framework and implementation of the framework to find the suitable combination of methods in each layer to produce satisfactory sentiment analysis accuracy. …”
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Interactive framework for dynamic modelling and active vibration control of flexible structures
Published 2008“…Controller-design strategies, parametric as well as nonparametric, are integrated within this framework. The design and implementation of the interactive learning system incorporating the simulation algorithms, modelling and control strategies, are developed using MATLAB. …”
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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
Published 2024“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…Java Media Framework library and the RTP protocol for audio transmission were used as development tools.The developed system designed in this thesis together with experimental results proved that the system could be implemented successfully. …”
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An improved diabetes risk prediction framework : An Indonesian case study
Published 2018“…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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New filtering framework for web personalization search / Anitawati Mohd Lokman and Aishah Ahmad
Published 2012“…This algorithm can be implemented in both website and search engine.…”
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…The research has proposed new implementation frameworks and new scripting language with the dynamic parameterization……”
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Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli
Published 2017“…Framework development methodology is used to make sure the prototype is successfully developed according to the schedule. …”
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A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection
Published 2023“…Ultimately, a working prototype will be developed to validate the framework using ant colony optimization and fuzzy logic. � 2013 Springer-Verlag.…”
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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid
Published 2023“…Initially, the Particle Swarm Optimization was implemented to establish the optimal sizes of DGs and the performance of the implemented algorithm was analyzed and quantified. …”
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Financial time series predicting using machine learning algorithms
Published 2013“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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