[PDF] Top 20 The Strategy of Building a Flood Forecast Model by Neuro-Fuzzy Network
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The Strategy of Building a Flood Forecast Model by Neuro-Fuzzy Network
... illustrate the practical application of the forecasting models, the Choshui River is used as a case ...study. The Choshui River is the longest river in Taiwan and is ... See full document
16
Counterpropagation fuzzy-neural network for city flood control system
... Summary The counterpropagation fuzzy-neural network (CFNN) can effectively solve highly non-linear control problems and robustly tune the complicated conversion of human intelligence to ... See full document
11
Neuro-Fuzzy Technology as a Predictor of Parathyroid Hormone Level in Hemodialysis Patients
... avoid the complexity of a model, it is not necessary to add other variables such as patient’s medications or dialytic prescriptions even though they are known to have a significant ... See full document
7
Fuzzy Clustering Neural Network as Flood Forecasting Model
... The FCNN has a hybrid learning scheme; the unsupervised learning scheme employs fuzzy min-max clustering to extract information from the input data.. The supervised learning scheme [r] ... See full document
16
Building a Player Strategy Model by Analyzing Replays of Real-Time Strategy Games
... control the use of limited resources, and create units and buildings in Real-Time Strategy(RTS) Games is a novel application in game ...player strategy models, and developing practical ... See full document
6
Heuristic fuzzy-neuro network and its application to reactive navigation of a mobile robot
... Abstract A novel pattern recognition approach to reactive navigation of a mobile robot is presented in this ...paper. A heuristic fuzzy- neuro network is developed for ... See full document
10
Neural network forecast model in deep excavation
... accuracy of ground movement prediction through finite element analyses heavily depends on the constitutive behavior of the ...soil. The soil parameters applied in constitutive models ... See full document
7
Fuzzy BP: A Neural Network Model with Fuzzy Inference
... According to the above descriptions, the medians aa', bb', and 2 will intersect at point g whose coordinate is denoted as (x,y). Thus, g is the centroid point of this triangle. The[r] ... See full document
6
Robust neuro-fuzzy model-following control of robot manipulators
... The interconnections compensating network can decompose the robot dynamics into decoupled subsystems and the fuzzy part approximates the unknown non-linearity of the robot[r] ... See full document
5
Efficiency Validation of Fuzzy Domain Theories Using a Neural Network Model
... Knowledge Base Evaluator ( D E ) [ 111 is an expert system that evaluates whether the expert system is suitable for a domain or not. Part of its rules is used to implement the [r] ... See full document
8
Neuro-fuzzy implementation of a self-tuning fuzzy controller
... In the first case, NF models for control rule-base and gain rule-base are separately trained with only 25 rules each, and they are used in parallel like in STFPIC; we denote this control[r] ... See full document
6
Building a Financial Forecast Model of Electronic Industry 施寶駒、林志忠、鄭華清
... all the companies listed in the stock exchange must make public their financial forecast at specific conditions for the reference of ...with the varieties of the ... See full document
2
Neuro-Fuzzy Cost Estimation Model Enhanced by Fast Messy Genetic Algorithms for Semiconductor Hookup Construction
... proposed model aims to systematically guide cost estimators to conduct their estimations for dealing with the above three cost-estimating ...See the right part of Figure 2. Namely, the ... See full document
18
Verifying Fuzzy Domain Theories Using a Neural Network Model
... In fuzzy rule verification, we propose a fuzzy rule clustering method to find the inconsistencies, which include redundant rules, conflicting rules and subsumed rules, in[r] ... See full document
6
Calculation of PID controller parameters by using a fuzzy neural network
... Department of Electrical and Control Engineering, National Chiao Tung University, Hsinchu 300, Taiwan, Republic of China 共Received 21 December 2001; accepted 13 July 2002兲 Abstract In this paper, we use ... See full document
10
Improve neuro-fuzzy learning by attribute reduction
... is a combination of neural networks and fuzzy systems to learn fuzzy rules from ...One of the popular tools for neuro-fuzzy learning is the Adaptive ... See full document
2
A Self-organization algorithm for real-time flood forecast
... method of data handing (GMDH) (Ivakhnenko, 1970, 1989; Ivakhnenko et ...cited by many scientists, GMDH is a useful data process for identifying complex systems, especially when only a small ... See full document
16
Setting a business strategy to weather the telecommunications industry downturn by using fuzzy MCDM
... deregulation, the exponential increase in internet IP applications, and the emergence of 3G broadband mobile services have created tremendous growth in the telecommunications industry in ... See full document
1
The Algorithmic Parameters of a Fuzzy Dynamic Learning Neural Network
... classification, the conventional neural network classifier represents training information in a one-pixel-one-class ...Therefore, the class mixture of a pixel cannot be taken ... See full document
12
A new method to forecast the TAIEX based on fuzzy time series
... i.e., the training data set and the testing data set. The training data set consists of the historical data from January to October for each year, and the testing data set ... See full document
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