In this study, the risk for road traffic accidents on Ubungo – Chalinze route (Tanzania) is comprehensively evaluated and analysed using fuzzy techniques. After identifying the main risk factors for road traffic accidents, the experts’ judgements are used to establish each single factor evaluation fuzzy set. Eventually, the single factor evaluation matrix is multiplied by the risk factor weight...

Sales forecasting is one of the most crucial issues addressed in business. Control and evaluation of future sales still seem concerned both researchers and policy makers and managers of companies. this research propose an intelligent hybrid sales forecasting system Delphi-FCBPN sales forecast based on Delphi Method, fuzzy clustering and Back-propagation (BP) Neural Networks with adaptive learni...

The objectives of this paper are two folds. The first one is to improve the time forecasting produced from the well known Earned Value Management (EVM), using the polynomial function. The time prediction observed from the polynomial model, which is compared against that observed from the most common method for time forecasting (critical path method), is a more accurate (mean absolute percentage...

The modern methods for power system load and energy prediction are usually based on artificial neural networks and fuzzy logic, which present satisfactory results. However, the estimation of the confidence intervals can not be applied directly, unlike to the classical forecasting methods. The objective of this paper is to present an optimized fuzzy logic method for midterm energy forecasting, w...

It has been hypothesized that number of road accidents and road casualties are increased in line with the raise in the variables of registered vehicles, population and road length. However, the effects of these variables toward road accidents are still inconclusive. Therefore, this paper develops models based on the variables which can be used to determine road accidents in Malaysia. In order t...

Recently a new approach was introduced in lightning protection incorporating the use of forecasting tools and preventive actions into one lightning protection system, the preventive lightning protection. The key feature of this protection system is that the hazard forecasting methods are planned according to the available preventive actions. The appropriate use of forecasting is very important ...

Forecasting tourism demand is a crucial issue in the tourism industry and is generally seen to be one of the most complex functions of tourism management. With the accurate forecasted trends and patterns that indicate the sizes, directions and characteristics of future international tourist flows, the government and private sectors can have a well-organized tourism strategy and provide a better...

artificial neural networks (anns) are flexible computing frameworks and universal approximators that can be applied to a wide range of time series forecasting problems with a high degree of accuracy. however, despite of all advantages cited for artificial neural networks, they have data limitation and need to the large amount of historical data in order to yield accurate results. therefore, the...

In the analysis of time invariant fuzzy time series, fuzzy logic group relationships tables have been generally preferred for determination of fuzzy logic relationships. The reason of this is that it is not need to perform complex matrix operations when these tables are used. On the other hand, when fuzzy logic group relationships tables are exploited, membership values of fuzzy sets are ignore...

This paper mainly deals with the design of forecasting model for Hydro power generation using Fuzzy time series. The fuzzy time series has recently received an increasing attention because of its capability of dealing with vague and incomplete data. There have been a variety of models developed either to improve forecasting accuracy or reduce computation overhead. This technique has been applie...