Fuzzy Rule Base

Chen et al. [24] provide a good review of Al techniques used for modeling environmental systems. Pongracz et al. [25] presents the application of a fuzzy-rule based modeling technique to predict regional drought. Artificial neural networks model have been applied for mountainous water-resources management in Cyprus [26] and to forecast raw-water quality parameters for the North Saskatchewan River [27]. 

Pongracz R, Bogardi I, Duckstein L (1999) Application of fuzzy rule-based modelling technique to regional drought. J Hydrol 224 100-114... 

Adriaenssens, V., Baets, B.D., Goethals, P.LM. and Pauw, N.D. (2004) Fuzzy rule-based models for decision support in ecosystem management, Sci. Total Environ., 319, pp. 1-12. 

Fuzzy inference systems are also known as fuzzy associative memories, fuzzy models, fuzzy-rule-based systems, or fuzzy controllers. 

Here, the premise is described by a membership function for the linguistic variable high and the function for the detection limit is the sum of the blank signal, y, and three times the standard deviation of the blank signal, Sg, (cf. Eq. (4.3)). Optimization of the parameters in the premise part of the rules is adaptively done by combining the fuzzy rule-based system with a neural network. Consider an adaptive neuro-fuzzy system with two inputs, and... 

Compare symbolic knowledge processing in case of crisp and fuzzy-rule-based systems. 

Chang, T. (1996), A Fuzzy Rule-Based Methodology for Dynamic Kanban Control in a Generic Kanban System, Ph.D. dissertation, Purdue University, West Lafayette, IN. 

Chang, T., and Yih, Y. (1998), A Fuzzy Rule-Based Approach for Dynamic control of kanbans in a generic kanban system, International Journal of Production Research, Vol. 36, No. 8, pp. 2247-2257. 

In conjunction with this fuzzy logic approach, a new chip-groove classification system was proposed, and the most significant geometric chip-groove parameters were identified from chip-groove profiles. A fuzzy rule-based system was developed based on the composite profile of the tool insert and its chip breakabiiity performance. 

Region Adaptive, Unsharp Masking Based Lanczos-3 Interpolation for 2-D Up-Sampling Crisp-Rule Versus Fuzzy-Rule Based Approach... 

Fuzzy logic controllers are governed by a set of if-then rule known as a knowledge base or rule base. The fuzzy rule base drives the inference engine to produce the output in response to one or a set of inputs. The knowledge base established on a heuristic approach is given as follows. 

Fig. 10 Subjective performance of the 20th frame of the akiyo sequence at 4 1 compression ratio using different interpolation techniques a Origintil, b Bicubic, c Lanczos-3, d DCT, e Crisp-rule based Lanczos-3 (Proposed-1), f Fuzzy-rule based Lanczos-3 (Proposed-2)...

This book chapter critically compares the capabilities and limitations of crisp-mle and fuzzy-rule based up-sampling techniques and their relevance in view of robustness, adaptability to varying constraints, complexities, quality enhancement and their effectiveness in real time applications. 

Generally, in a terrestrial communication system, a transmitter possesses more processing ability than the receiver. Therefore, the major computational burden is easily taken up by the transmitter and less computational burden is left for the receiver. Since the proposed method is based on a preprocessing approach, it imparts more computational burden on the transmitting side than the receiving end and thus makes the receiver computationally less complex, fast and suitable for various real time applications. In addition, since this method is a spatial domain approach, it is computationally less complex than transform domain techniques such as DCT and wavelet. The proposed fuzzy-rule based method is a low complex, highly flexible and efficient technique that works fine with all types of video data. 

The relationships between the IFs and the degradation states reached are not completely known they are obtained from information on literature models, whose parameters are often uncertain or not completely known, some scarce statistical data available and expert knowledge of qualitative nature. The model of the degradation process should be able to handle such epistemic uncertainties in this work, a fuzzy logic approach is proposed, in which the link between the IFs and the degradation states is described by means of Fuzzy Rule Bases (FRBs). 

Define the set of fuzzy inference rules (Fuzzy Rule Base, FRB), which relate the linguistic terms (fuzzy sets) of the input physical variables to those of the output level of the IF considered. 

Liu, J., Yang, J.B., Wang, J. and Sii, H. (2005), Engineering System Safety Analysis and Synthesis using the Fuzzy Rule-based Evidential Reasoning Approach, Quality and Reliability Engineering International, Vol. 21, No. 4, pp. 387 11. 

Yang, Z.L., Bonsall. S. and Wang, J. (2008), Fuzzy Rule-Based Bayesian Reasoning Approach for Prioritization of Failures in FME A, IEEE Transactions on Reliability, Vol. 57, No. 3, pp. 517-528. 

Figure 7, if the first input is SP and the second input is BN, then the output is zero. Table 6 shows the obtained fuzzy rule base from Figure 7a. As mentioned, the output of the fuzzy system is triangular membership functions which lie between 0 and 0.5. Therefore, the damping value can guarantee the stability of the structure, and STMD system always acts as an under damped system. The design variables are P, P 6, m, (3 and that should be designed...

Qian, Y. and Zhang, P.R., 1999, Fuzzy rule-based modeling and simulation of imprecise units and processes, Canadian J. Chemical Engineering, 77(1), 186. 

We can also use fuzzy rules (based on fuzzy logic theory) to produce excellent results [TEK07 SOL 11], or indeed neural networks, adaptive or otherwise [MOR 06],... 

Zhao, C. H., et al., A Fuzzy Rule Based Automatic V/P Transfer System for Thermoplastic Injection Molding, SPE-ANTEC, 1997. 

The fuzzy rule base that is found for a cluster merging threshold value of 0.2 are ... 

The marine industry is recognising the need for powerful techniques that can be used to perform risk analysis of marine systems. One technique that has been applied in both national and international marine regulations and operations is Failure Mode and Effects Analysis (FMEA). This risk analysis tool assumes that a failure mode occurs in a system/component through some failure mechanism. The effect of this failure is then evaluated. A risk ranking is produced in order to prioritise the attention for each of the failure modes identified. The traditional method utilises the Risk Priority Number (RPN) ranking system. This method determines the RPN by finding the multiplication of factor scores. The three factors considered are probability of failure, severity and detectability. Traditional FMEA has been criticised to have several weaknesses. These weaknesses are addressed in this Chapter. A new approach, which utilises the fuzzy rules base and grey relation theory, is presented. 

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