Applied Soft Computing, Journal Year: 2023, Volume and Issue: 148, P. 110902 - 110902
Published: Oct. 5, 2023
Language: Английский
Applied Soft Computing, Journal Year: 2023, Volume and Issue: 148, P. 110902 - 110902
Published: Oct. 5, 2023
Language: Английский
Deleted Journal, Journal Year: 2024, Volume and Issue: 2, P. 80 - 88
Published: Jan. 30, 2024
This study adopted a decision system model that includes machine learning (ML) and multi-criteria decision-making (MCDM) for thyroid prediction analysis. Many people face disease, so the early of this disease can aid around world in treatment. paper integrates ML algorithms with MCDM methodology. Three are used paper: logistic regression (LR), support vector (SVM), random forest classifier (RF). These to predict analyse disease. The results show RF has highest accuracy, precision, F1 score. 0.95 accuracy. SVM 1.0 recall Then, methodology is various criteria rank use best algorithm. TOPSIS method as an algorithms. mean compute weights. algorithm paper, followed by SVM, worst LR.
Language: Английский
Citations
5Lecture notes in networks and systems, Journal Year: 2025, Volume and Issue: unknown, P. 334 - 345
Published: Jan. 1, 2025
Language: Английский
Citations
0Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: unknown
Published: April 28, 2023
Language: Английский
Citations
12Systems, Journal Year: 2023, Volume and Issue: 11(8), P. 397 - 397
Published: Aug. 2, 2023
Engineering and technological breakthroughs in sustainability play a crucial role reducing carbon emissions. An important aspect of this is the active participation enterprises addressing reduction as systemic approach. In response to government incentives People’s Republic China, Chinese have developed systems align their organizational goals with national long-term plans. This paper evaluates schemes employed by six companies multi-criteria decision-making (MCDM) problem. To end, we propose new hybrid MCDM method called grey-MEREC-MAIRCA method. combines recently based on removal effects criteria (MEREC) for weighting multi-attribute ideal-real comparative analysis (MAIRCA) grey system theory. The proposed provides additional benefit accounting uncertainty decision making. Notable findings research, decision-maker scores, are that control direct emissions energy-saving efficiency top priorities. contrast, committing corporate social responsibility through public welfare information disclosure considered lesser Furthermore, ranking results obtained using compared those from classical weighted sum model technique order preference similarity ideal solution (TOPSIS), confirming selection best company. Despite limitation steps needed evaluation, it opens up opportunities future research develop simpler methods under uncertainty.
Language: Английский
Citations
11Applied Soft Computing, Journal Year: 2023, Volume and Issue: 148, P. 110902 - 110902
Published: Oct. 5, 2023
Language: Английский
Citations
11