Search Results - subject:"fuzzy inference system"

Prediction the Groundwater Level of Bastam Plain (Iran) by Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS)

Emamgholizadeh, Samad; Moslemi, Khadije; Karami, … - In: Water Resources Management 28 (2014) 15, pp. 5433-5446

Neuro-Fuzzy Inference System (ANFIS) in the forecasting of the groundwater level of Bastam Plain in Iran. For this purpose …

Persistent link: https://www.econbiz.de/10011151764

Estimation of the Change in Lake Water Level by Artificial Intelligence Methods

Buyukyildiz, Meral; Tezel, Gulay; Yilmaz, Volkan - In: Water Resources Management 28 (2014) 13, pp. 4747-4763

(MLP), Radial Basis Neural Networks (RBNN) and Adaptive Network Based Fuzzy Inference System (ANFIS), were used to estimate …

Persistent link: https://www.econbiz.de/10010997841

An evolutionary-based adaptive neuro-fuzzy inference system for intelligent short-term load forecasting

Kazemi, S. M. R.; Hoseini, Mir Meisam Seied; … - In: International transactions in operational research : … 21 (2014) 2, pp. 311-326

Persistent link: https://www.econbiz.de/10010256672

A neuro-fuzzy combination model based on singular spectrum analysis for air transport demand forecasting

Xiao, Yi; Liu, John J.; Wang, Yingfeng; Lai, Kin Keung; … - In: Journal of air transport management 39 (2014), pp. 1-11

Persistent link: https://www.econbiz.de/10010400146

A hybrid model based on ANFIS and adaptive expectation genetic algorithm to forecast TAIEX

Wei, Liang-Ying - In: Economic Modelling 33 (2013) C, pp. 893-899

hybrid model utilizes an adaptive expectation genetic algorithm to optimize adaptive network-based fuzzy inference system …) employ fuzzy inference system (FIS) to build linguistic rules from the linguistic technical indicator dataset and optimize …

Persistent link: https://www.econbiz.de/10010738039

Estimating Daily Pan Evaporation Using Different Data-Driven Methods and Lag-Time Patterns

Kim, Sungwon; Shiri, Jalal; Kisi, Ozgur; Singh, Vijay - In: Water Resources Management 27 (2013) 7, pp. 2267-2286

inference system (ANFIS). Daily PE was estimated at Daegu and Ulsan stations using temperature-based, radiation-based, sunshine … perceptron-neural networks model (MLP-NNM), generalized regression neural networks model (GRNNM), and adaptive neuro-fuzzy …

Persistent link: https://www.econbiz.de/10010794773

Water Quality Zoning Using Probabilistic Support Vector Machines and Self-Organizing Maps

Nikoo, Mohammad; Mahjouri, Najmeh - In: Water Resources Management 27 (2013) 7, pp. 2577-2594

Machines (PSVMs) and Fuzzy Inference System (FIS). The required data for training the PSVM is generated by using the FIS in a …

Persistent link: https://www.econbiz.de/10010794805

Integrating materials management with project management of complex projects

Dixit, Vijaya; Srivastava, Rajiv Kumar; Chaudhuri, Atanu - In: Journal of Advances in Management Research 10 (2013) 2, pp. 230-278

items are hidden in nature and are difficult to measure and model mathematically. Hence, Fuzzy Inference System (FIS), which …

Persistent link: https://www.econbiz.de/10014840028

Examination of Relationship Between Stock Returns and Factors Affecting Capital Structure and Financial Ratios with ANFIS Method: An Application on ISE 100 Index

Yoruk, Nevin; Karaca, S. Serdar; Hekim, Mahmut; Tuna, … - In: Anadolu University Journal of Social Sciences 13 (2013) 2, pp. 101-114

In this study, the stock return rate of the company shares was estimated by means of the adaptive neuro-fuzzy inference … system (ANFIS). For this aim, the data of financial ratios prepared for the input and output variables of the ANFIS was …

Persistent link: https://www.econbiz.de/10010676197

The nonlinear effect of green innovation on the corporate competitive advantage

Chen, Yu-Shan; Chang, Ke-Chiun - In: Quality & Quantity: International Journal of Methodology 47 (2013) 1, pp. 271-286

This study uses Adaptive Neuro-Fuzzy Inference System (ANFIS) to explore the nonlinear relationships between green …

Persistent link: https://www.econbiz.de/10010634200