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Neuro-Fuzzy and Particle Swarm Optimization based Model for the Steam and Cooling sections of a Cogeneration and Cooling Plant by Alemu Lemma, Tamiru, Rangkuti, Chalillullah, Mohd Hashim, Fakhruldin

“…Neuro-fuzzy approach trained by a sequence of optimization algorithms-Particle Swarm Optimization (PSO) followed by Back-Propagation (BP)-is used to develop models for the steam drum pressure, steam drum water level, steam flow rate and chilled water supply temperature. …”
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Risk assessment for safety and health algorithm for building construction in Oman by Al-Anbari, Saud Said

“…Risk assessment matrices are widely used to evaluate risks related to such hazards. …”
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SYSTEMATIC DESIGN ALGORITHM FOR ENERGY EFFICIENT AND COST EFFECTIVE HYDROGEN PRODUCTION FROM PALM WASTE by INAYAT, ABRAR

“…In the current study, a systematic autonomous algorithm incorporating reaction kinetics model, flowsheet calculations, heat integration analysis and economic evaluation, has been developed to calculate optimum parameters giving minimum hydrogen production cost using optimization strategies. …”
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Optimization of stiffened panel fatigue life by using finite element analysis by Mazlan, Shahan

“…The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

“…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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Temperature control of a pilot plant reactor system using a genetic algorithm model‐based control approach by Wahab, Ahmad Khairi Abdul, Hussain, Mohd Azlan, Omer, Rosli

“…The work described in this paper aims at exploring the use of an artificial intelligence technique, i.e. genetic algorithm (GA), for designing an optimal model-based controller to regulate the temperature of a reactor. …”
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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques by Salem S. M. Khalifa

“…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. …”

Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization by Dasril, Yosza, Muslim, Much Aziz, Al Hakim, M. Faris, Jumanto, Jumanto, Prasetiyo, Budi

“…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 by Yosza Dasril, Yosza Dasril, Muslim, Much Aziz, Al Hakim, M. Faris, Jumanto, Jumanto, Budi Prasetiyo, Budi Prasetiyo

“…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 by Yosza Dasril a, Yosza Dasril a, Muslim, Much Aziz, Al Hakim, M. Faris, Jumanto, Jumanto, Budi Prasetiyo, Budi Prasetiyo

“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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Industrial implementation of machine learning forecasting algorithms for large-scale Solar Heat for Industrial Process (SHIP) Systems by Manu, Abdurrahman, Haja Mohideen, Ahmad Jazlan, Akhter, Muhammad Naveed, Ahmad Huzri, Muhammad Danial, Mohd Ibrahim, Azhar, Mohd Zaki, Hasan Firdaus, Sreeram, Victor

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Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization by Yosza Dasril, Yosza Dasril, Much Aziz Muslim, Much Aziz Muslim, M. Faris Al Hakim, M. Faris Al Hakim, Jumanto, Jumanto, Budi Prasetiyo, Budi Prasetiyo

“…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 by Yosza Dasril, Yosza Dasril, Much Aziz Muslim, Much Aziz Muslim, M. Faris Al Hakim, M. Faris Al Hakim, Jumanto, Jumanto, Budi Prasetiyo, Budi Prasetiyo

“…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 by Yosza Dasril, Yosza Dasril, Much Aziz Muslim, Much Aziz Muslim, M. Faris Al Hakim, M. Faris Al Hakim, Jumanto, Jumanto, Budi Prasetiyo, Budi Prasetiyo

“…Machine learning algorithm such as LightGBM can be used to evaluate credit risk. …”
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BCLH2Pro: a novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes by Tuntiwongwat, Thanadol, Thammawiset, Sippawit, Srinophakun, Thongchai Rohitatisha, Ngamcharussrivichai, Chawalit, Sukpancharoen, Somboon

“…The study proposes an integrated Fe2O3-based ฺBCLpro combining steam gasification for H2 production. …”
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Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…The first experiment revealed that the Algorithm Adaptation framework outperformed Problem Transformation methods across most metrics. …”
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Data mining techniques for disease risk prediction model: A systematic literature review by Ahmad W.M.T.W., Ghani N.L.A., Drus S.M.

Modeling forest fires risk using spatial decision tree by Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin, Sitanggang, Imas Sukaesih

“…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 by Wang, B., Li, Y., Wang, S., Watada, J.

“…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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A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

“…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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