scholarly journals Membership Function Optimization of Fuzzy Inference System Using Cuckoo Search Algorithm for Peak Load Forecasting in National Holiday

2021 ◽  
Vol 5 (2) ◽  
pp. 74-79
Author(s):  
Andi Imran ◽  
Imam Robandi ◽  
Firdaus Firdaus ◽  
Ruslan Ruslan ◽  
Muhammad Yusuf Mappeasse ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Membership Function ◽  
Search Algorithm ◽  
Peak Load ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Fuzzy Logic System ◽  
Electricity System ◽  
Peak Loads ◽  
Logic System

This study aims to analysis peak load prediction of Indonesian national holidays for Jawa-Bali electricity system. Forecasting applied using the Fuzzy Logic System (FLS) method combined with the Cuckoo Search Algorithm (CSA). CSA is used to determine the optimal membership function in fuzzy logic. Cuckoo search algorithm has a very good performance in terms of optimization. This method is applied for short-term load estimates on holidays/special days on the Jawa-Bali electricity system, Indonesia. The study used data from daily peak loads during Indonesian national holidays in 2014 on the Jawa-Bali electricity system. The data analyzed is the daily peak load documentation data for 4 days before national holidays and during national holidays in 2014. Testing the simulation results, it was found that the Fuzzy Logic System - Cuckoo Search Algorithm (FLS-CSA) method gives good forecasting results, this is evidenced by using the mean absolute percentage error (MAPE). Forecasting results using the Cuckoo Search Algorithm (CSA) optimization method on fuzzy logic membership functions for peak loads on national holidays on the Java-Bali 500kV electrical system give satisfactory results with an average forecasting error of 1.511314562%.

Logistics Demand Forecasting with Asymmetry-Width Probabilistic Fuzzy Logic System

2013 ◽  
Vol 706-708 ◽  
pp. 2012-2016
Author(s):  
Zhong Wei Wang ◽  
Li Xin Lu
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Membership Function ◽  
Fuzzy Set ◽  
Demand Forecasting ◽  
Fuzzy Logic System ◽  
The Asymmetry ◽  
Logistics Demand ◽  
Better Than ◽  
Logic System

There are a lot of approaches in logistics demand forecasting field and perform different characters. The probabilistic fuzzy set (PFS) and probabilistic fuzzy logic system is designed for handling the uncertainties in both stochastic and nonstochastic nature. In this paper, an asymmetric probabilistic fuzzy set is proposed by randomly varying the width of asymmetric Gaussian membership function. And the related PFLS is constructed to be applied to a logistics demand forecasting. The performance discloses that the asymmetry-width probabilistic fuzzy set performs better than precious symmetric one. It is because the asymmetric probabilistic fuzzy sets variability and malleability is higher than this of the symmetric probabilistic fuzzy set.

scholarly journals Fuzzy optimization based Water Distribution Network design using Self-Adaptive Cuckoo Search Algorithm

2021 ◽  
Author(s):  
A. Vasan ◽  
K. Srinivasa Raju ◽  
B. Sriman Pankaj
Keyword(s):  
Membership Function ◽  
Water Distribution ◽  
Search Algorithm ◽  
Fuzzy Optimization ◽  
Optimal Solution ◽  
Water Distribution Network ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions

Abstract Water Distribution Network(s) (WDN) design is gaining prominence in the urban planning context. Several factors that play a significant role in design are uncertainty in data, non-linear relation of head loss & discharge, combinatorial nature of the problem, and high computational requirements. In addition, many conflicting objectives are possible and required for effective WDN design, such as cost, resilience, and leakage. Most of the research work published has used multiobjective evolutionary optimization in solving such complex WDN. However, the challenge of such population based evolutionary approaches is that they provide multiple trade-off Pareto optimal solutions to the decision-maker who will have to choose another set of techniques to arrive at a single optimal solution. The present study employs a fuzzy optimization approach that would provide a single optimal WDN design for Hanoi and Pamapur, India. Maximization of network resilience (NR) and minimization of network cost (NC) are employed in a multiobjective context. Later, minimization of network leakages (NL) is also incorporated, leading to three objective problems. Hyperbolic Membership Function (HMF), Exponential Membership Function (EMF), and Non-linear Membership Function (NMF) are employed in Self-Adaptive Cuckoo Search Algorithm based fuzzy optimization. HMF is found suitable to determine the best possible WDN design for chosen case studies based on the highest degree of satisfaction. HIGHLIGHT Most of the research conducted till now have used evolutionary multiobjective optimization in solving WDNs. But, the challenge of such evolutionary approaches is that they provide multiple trade-off pareto optimal solutions to the decision maker who will have to further choose another methodology to converge to a single optimal solution. The proposed methodology would simplify the decision-making process for an engineer.

Minimum zone sphericity evaluation based on a modified cuckoo search algorithm with fuzzy logic

2018 ◽  
Vol 30 (1) ◽  
pp. 015008
Author(s):  
Jingzhi Huang ◽  
Lin Jiang ◽  
Xiangzhang Chao ◽  
Jiubin Tan
Keyword(s):  
Fuzzy Logic ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Minimum Zone
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