Various methods are currently used in travel demand modelling (TDM), for example, the Four-Step model, which is widely used and is perhaps the most famous one, Discrete Choice Models, Fuzzy Set Theory and the Neural Network Approach. The emergence of these different methods is due to, for instance, different areas having different problems. Hence, a method successfully applied in one area could...

Disasters can cause many casualties and considerable destruction mainly because of ineffective preventive measures, incomplete preparedness, and weak relief logistics systems. After catastrophic events happen, quick and effective response is of great importance, so as to having an efficient logistic plan for distributing needed relief commodities efficiently and fairly among affected people. In...

An organization has to make the right decisions in time depending on demand information to enhance the commercial competitive advantage in a constantly fluctuating business environment. Therefore, predicting the future quantity for the next period most likely appears to be crucial. This work presents a comparative forecasting methodology regarding to uncertain customer likings in a movie domain...

This paper proposes a fuzzy inference based neural network for the forecasting of short term loads. The forecasting model is the integration of fuzzy inference engine and the neural network, known as Fuzzy Inference Neural Network (FINN). A FINN initially creates a rule base from existing historical load data. The parameters of the rule base are then tuned through a training process, so that th...

In this paper, we proposed the membership function modification in Fuzzy Support Vector Machine (Fuzzy SVM) based on exponential distribution function. This function is expressed as the level of training data contribution to its class model building. It is formed prior to training phase and started with checking and handling the missing values. Afterwards is the formation of fuzzy variables bas...

Recently the number of distance education platforms has been increased significantly. These platforms provide isolation between the student and teacher. Thus, there is a need for predicting the students who are possible to fail in a specific course and take the precautions like starting face-to-face on demand lectures for individual cases. Both of artificial intelligence and data mining techniq...

Manpower recruitment and training in uncertain and turbulent environments is a challenge to decision makers in large organizations. In the absence of numerical precision on market growth and the ensuing manpower demand, designing manpower planning policies is vital. Often times, companies incur losses due to overstaffing and/or understaffing. For instance, organizations lose business when criti...

The purpose of this paper is to extend [Ouyang, L. Y., Chuang, B. R. (2001). A periodic review inventory-control system with variable lead time. International Journal of Information and Management Sciences, 12, 1–13] periodic review inventory model with variable lead time by considering the fuzziness of expected demand shortage and backorder rate. We fuzzify the expected shortage quantity at th...