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Showing 2 results for Fuzzy Inference System
Forecasting the Long Run Electricity Demand Using Hybrid PSO-ANFIS Algorithm
Dr Hossein Sadeghi, Dr Ali Akbar Afzalian, Dr Mahmood Haghani, Hossein Sohrabi Vafa,
Volume 3, Issue 10 (12-2012)
Abstract

  Storing the electrical energy in large scale is impossible. So, it is necessary to identify the factors affecting the electricity demand. Researchers have used different methods to forecast the future demand of electricity, among them intelligent methods and fuzzy based methods are more popular. Since ANFIS structure is based on researcher’s experience about phenomenon, the created structure may not have the best result. Therefore, we used PSO-ANFIS structure.

  In this paper long term electricity demand is forecasted until the year 2025 by hybrid PSO-ANFIS algorithm. The results confirm the high power of the Adaptive Neural based Fuzzy Inference System in forecasting the electricity demand. Results also indicate that the forecasted electricity demand will be 401 billion KWh in 2025. The prediction performance of the proposed technique is more accurate than the ARIMA model.


A Systematic Approach for Asset Liability Management of Pension Funds in a Fuzzy Environment
Hamidreza Izadbakhsh, Ahmad Soleymanzadeh, Hamed Davari Ardakani, Marzieh Zarinbal,
Volume 8, Issue 29 (10-2017)
Abstract
Since pension funds are among the most important and effective organizations in economic and social environments, it is critical to study their problems ahead. Asset and liability management (ALM) is a useful tool to study pension funds and their stakeholders. This paper tries to understand the key factors effecting on ALM and to analyze them using system dynamics. Fuzzy inference engine is also used to quantify the important risks in ALM. Results show that considering ALM and stakeholders’ benefits as whole and paying attention to risk factors such as changing population are the key factors for successful ALM.

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