Multipurpose Decision Support System Framework







This research proposed a decision support system framework that can able to perform probability, optimization, regression, estimation and clustering operation in inferencing the decision. Furthermore, the framework is prepared for cloud-based applications and can be easily integrated into other applications by providing API functions.

For probabilities cases, the method will consist of Analytical Hierarchy Process (AHP), Bayes, Comparative Performance Index (CPI), Delphi Method, Demster-Shafer,  Equal Likelihood, Exponential Comparison, Hurwitch, Minimax Regression.

The optimization will consist of Linear Programming (Big M Minimization, Dual Minimization, Simplex Maximation) and Genetic Algorithm.

Regression decision-making could be performed by using Backpropagation Neural Network, Gradient Descent, Linear Regression, Least Square Criterion.

Lastly, the clustering and estimation will be used respectively the Self Organizing Maps (SOM) and Mamdani Fuzzy Inference System.

The decision support system developed using this framework would allow users to select any decision method with the same input. The import functions are also available for users to upload data or other systems to import data then calculate the results.



Decision Support System, Probabilistic, Optimization, Regression, Clustering, Estimation.