Search Results - (( development case function algorithm ) OR ( java data prediction algorithm ))
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1
Mapreduce algorithm for weather dataset
Published 2017“…In addition, these characteristics also contribute to the complexity on the data processing and prediction. Big Data analytics is a new concept to process the Big Data. …”
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2
MapReduce algorithm for weather dataset
Published 2018“…In addition, these characteristics also contribute to the complexity on the data processing and prediction. Big Data analytics is a new concept to process the Big Data. …”
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Research Report -
3
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This prediction can be made by cluster the new data with the old data and observe where the data belongs. …”
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4
AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…Besides, an android application is being cre-ated to give therapy based on machine learning predictions. To collect data, we enlisted the help of 4,500 people. …”
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5
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…Thus, there is a need to automate the process of identifying and predicting (positive, negative, or neutral class) these cyber-trooping data. …”
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6
AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…Besides, an android application is being cre-ated to give therapy based on machine learning predictions. To collect data, we enlisted the help of 4,500 people. …”
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7
The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment
Published 2016“…Thus, a new algorithm known as infection evolution (IE) was developed in this study. …”
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8
Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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9
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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10
An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…Performance of each algorithm is compared in terms of number of test cases generated as well as the run time required. …”
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11
Input Information in the Approximate Calculation of Two-Dimensional Integral from Highly Oscillating Functions (Irregular Case)
Published 2019“…There are the cases when input information about function is given on the set of traces of the function on planes, the set of traces of the function on lines, and the set of values of the function in the points. …”
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Conference or Workshop Item -
12
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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13
Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…New Iterative Alternating Group Explicit (NAGE) is a powerful parallel numerical algorithm for multidimensional temperature prediction. …”
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14
Development of symbolic algorithms for certain algebraic processes
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Monograph -
15
Development of symbolic algorithms for certain algebraic processes
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Monograph -
16
Online Programming Judge System (UOJ)
Published 2013“…Moreover, the mechanism of test cases generation using PSO algorithm is deeply analyzed. …”
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Final Year Project -
17
Improvement and application of particle swarm optimization algorithm
Published 2025“…An ideal assignment technique assigns new duties to each functioning robot, followed by evolutionary algorithms and Particle Swarm Optimization (PSO) to design pathways to the reconfigured positions. …”
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18
Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals
Published 2012“…However, the GA outperforms the SA algorithm in medium and large size test cases. Sensitivity analysis shows that value of the objective function decreases as the number of available AGVs increases. …”
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19
Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024“…The second-level learner uses logistic regression (LR) to aggregate the final prediction output. The landslide data together with its conditioning factors (feature variables) collected from three districts in the Central Java Province, Indonesia, has been used as the case study for the LSM. …”
Conference Paper -
20
A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…TCP factors and a weighted fitness function are also used for test case optimisation. …”
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