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Journal ArticleDOI

Predicting injection profiles using ANFIS

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TLDR
Experiments demonstrate that although soft computing methods are somewhat of tolerant of inaccurate inputs, cleaned data results in more robust models for practical problems, due to its simplicity in parameter selection and its fitness in the target problem.
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This article is published in Information Sciences.The article was published on 2007-10-01. It has received 103 citations till now. The article focuses on the topics: Adaptive neuro fuzzy inference system & Soft computing.

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Industrial applications of fuzzy control

道夫 菅野
TL;DR: This work focuses on the application of Fuzzy and Artificial Intelligence Methods in the Building of a Blast Furnace Smelting Process Model and the development of Performance Adaptive FuzzY Controllers with Application to Continuous Casting Plants.
Journal ArticleDOI

The application of ANFIS prediction models for thermal error compensation on CNC machine tools

TL;DR: This paper first reviews different methods of designing thermal error models, before concentrating on employing an adaptive neuro fuzzy inference system (ANFIS) to design two thermal prediction models that show that the ANFIS-FCM model is superior in terms of the accuracy of its predictive ability with the benefit of fewer rules.
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Evapotranspiration estimation by two different neuro-fuzzy inference systems

TL;DR: Based on the comparisons, it is found that the S-ANFIS model yields plausible accuracy with fewer amounts of computations as compared to the G- ANFIS and MLP models in modeling the ET0 process.
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River Flow Estimation and Forecasting by Using Two Different Adaptive Neuro-Fuzzy Approaches

TL;DR: In this article, two different adaptive neuro-fuzzy (ANFIS) techniques for the estimation of monthly streamflows were evaluated and the results indicated that the performance of the ANFIS-SC model was slightly better than the AN FIS-GP model in streamflow forecasting.
References
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Fuzzy sets

TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Journal ArticleDOI

ANFIS: adaptive-network-based fuzzy inference system

TL;DR: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference System implemented in the framework of adaptive networks.
Book

Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence

TL;DR: This text provides a comprehensive treatment of the methodologies underlying neuro-fuzzy and soft computing with equal emphasis on theoretical aspects of covered methodologies, empirical observations, and verifications of various applications in practice.
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Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review]

TL;DR: Interestingly, neuro fuzzy and soft computing a computational approach to learning and machine intelligence that you really wait for now is coming.
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Fuzzy Model Identification Based on Cluster Estimation

TL;DR: An efficient method for estimating cluster centers of numerical data that can be used to determine the number of clusters and their initial values for initializing iterative optimization-based clustering algorithms such as fuzzy C-means is presented.