An application of fuzzy collaborative intelligence to unit cost forecasting with partial data access by security consideration

Due to security considerations, integral access to unit cost data is often limited. As a result, it becomes extremely difficult to accurately predict unit cost. To solve this problem, a fuzzy collaborative forecasting approach is proposed in this study. In the proposed methodology, every expert uses a Fuzzy Linear Regression (FLR) equation to predict the unit cost. Subsequently, rather than the raw data, the forecasting results by an expert are conveyed to other experts to modify their settings, so that the actual values will be contained in the fuzzy forecasts after collaboration.