Search Results - (( model evaluation methods algorithm ) OR ( java application learning algorithm ))
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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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Thesis -
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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The project objectives includes:(i) To investigate lightweight message encryption algorithms by benchmarking their efficiency in terms of computation speed and generated cipher text size; (ii) To design and develop the TalkOut mobile application with lightweight message encryption by using prototype software development model.; and (iii) To evaluate the usability performance of the developed proposed TalkOut mobile application using System Usability Scale (SUS) approach. …”
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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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Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting
Published 2013“…These algorithms include equal�weights combination of Best NN models, combination of trimmed forecasts, combination through Variance-Covariance method and Bayesian Model Averaging. …”
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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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Unifying the evaluation criteria of many objectives optimization using fuzzy Delphi method
Published 2021“…Thus, unify a set of most suitable evaluation criteria of the MaOO is needed. This study proposed a distinct unifying model for the MaOO evaluation criteria using the fuzzy Delphi method. …”
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Evaluating the effectiveness of integrated benders decomposition algorithm and epsilon constraint method for multi-objective facility location problem under demand uncertainty
Published 2017“…For this aim, a multi-objective facility location allocation model is proposed. In this case, an integrated BDA and epsilon constraint method are proposed and it is shown that how Pareto points in multi-objective facility location model can be found. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods
Published 2021“…The evaluation criteria of Many Objective Optimization algorithm (MaOO) play a critical role in evaluating the competition MaOO algorithms. …”
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Incorporating the range-based method into GridSim for modeling task and resource heterogeneity
Published 2017“…In this paper, we propose a new simulation model that incorporates the range-based method into GridSim for modeling and simulating heterogeneous tasks and resources in order to capture the inherent heterogeneity of Grid environments that later can be used by other researchers to test their algorithms.…”
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Evaluation of Lightning Current Using Inverse Procedure Algorithm.
Published 2013“…The proposed method considers on all electromagnetic fields components and can evaluate full shape of current, velocity and constant parameters of current models in contrast with previous studies. …”
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Hybrid performance measures and mixed evaluation method for data classification problems
Published 2012“…In fact, no previous studies employ mixed evaluation method in evaluating and comparing the performance measures. …”
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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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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market
Published 2024“…By setting the ML algorithms and their parameter along with using Walk-Forward Analysis (WFA) method, the algorithm design of trading signal was evaluated based on two groups of evaluation indicators, namely directional and performance. …”
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Development of an Automated Technique for Reconstructing Jawi Characters in Historical Documents
Published 2007“…A noise model has been developed to test the reliability of the proposed algorithm. …”
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Visualisasi pohon sintaksis berasaskan model dan algoritma sintaks ayat bahasa Melayu
Published 2018“…To achieve these objectives (the algorithm, the model and the X-bar rules), five phases of research methods involved namely identifying the research gap, the sentence and rules categorization, model and algorithm design phase, prototype development evaluation and conclusion phase. …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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