Search Results - (( risk evaluation method algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan
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Risk assessment for safety and health algorithm for building construction in Oman
Published 2015“…Risk assessment matrices are widely used to evaluate risks related to such hazards. …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…Under the background of big data, it is of practical significance to prevent loan risk by the machine learning algorithm. Aiming at the characteristics of unbalanced loan data and high noise, this paper proposes an improved Gray Wolf optimization strategy (PSOEBGWO). …”
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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques
Published 2024“…Two methods were used to validate the proposed architecture, that is, the analytical method was used to validate the neuro-fuzzy risk assessment model and the safe path selection model, whereas the experimental method was used to evaluate the prototype. …”
thesis::doctoral thesis -
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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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Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization
Published 2023“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout
Published 2025“…The first experiment revealed that the Algorithm Adaptation framework outperformed Problem Transformation methods across most metrics. …”
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Thesis -
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Data mining techniques for disease risk prediction model: A systematic literature review
Published 2023Conference Paper -
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Modeling forest fires risk using spatial decision tree
Published 2011“…In addition, criteria evaluation and weighting method are most applied to evaluate the small problem containing few criteria. …”
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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio
Published 2018“…Considering nonstatistical uncertainties and/or insufficient historical data in security return forecasts, fuzzy set theory has been applied in the past decades to build portfolio selection models. Meanwhile, various risk measurements such as variance, entropy and Value-at-Risk have been proposed in fuzzy environments to evaluate investment risks from different perspectives. …”
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