Adaptive Networks

The Adaptive Network based Fuzzy Inference System (ANFIS)... 

Jang, J.S.R. (1993) ANFIS Adaptive Network-based Fuzzy Inference System, IEEE Transactions on Systems, Man and Cybernetics, 23, pp. 665-685. 

Strang. G., Wavelets and dilation equations A brief introduction. SIAM Rev. 31, 614 (1989). Ungar, L. H., Powell, B. A., and Kamens, S. N., Adaptive Networks for fault diagnosis and process control. Comput. Chem. Eng. 14, 561 (1990). 

Broomhead, D. S. Lowe, D. Multivariable functional interpolation and adaptive networks. Complex Syst. 1988, 2,312-355. 

In this paper we describe the application of an adaptive network based fuzzy inference system (ANFIS) predictor to the estimation of the product compositions in a binary methanol-water continuous distillation column from available on-line temperature measurements. This soft sensor is then applied to train an ANFIS model so that a GA performs the searching for the optimal dual control law applied to the distillation column. The performance of the developed ANFIS estimator is further tested by observing the performance of the ANFIS based control system for both set point tracking and disturbance rejection cases. 

Broomhead, D.S., and Lowe, D., Multi-variable Eunctional Interpolation and Adaptive Networks, Complex Systems, 2, 321, 1988. 

Jang, J.S.R., ANFIS Adaptive-network-based fuzzy inference systems, IEEE Trans. Syst. Man... 

The resulting models are referred to by various names, including neural networks, neurocomputers, Parallel Distributed Processing (PDP) models, neuromorphic systems, layered self-adaptive networks, and connectionist models. Here, we use the name neural networks, or neural nets for short. We use these networks as vehicles for adaptively developing the coefficients of decision function via successive presentations of training sets of patterns. 

These networks are termed market-driven value networks. Market-driven snpply chains are adaptive networks that can quickly align organizations market to market focnsed on delivering a value-based... 

The behavior of adaptive chemical systems can be conceptualized in terms of adaptive networks. Such a representation also applies to adaptive materials, and in particular to dynamic polymers. I shall recall here some points made earlier [41, 43,116] and present some additional aspects that will be expanded in more detail on another occasion. 

Fig. 12 Adaptive networks of constitutional dynamic polymers. Two-dimensional network representation of the effector-driven adaptation of the set of dynamers PI, P2, P3, and P4 in response to a chemical effector, the sodium cation Na" (see Fig. 11). The initial, close to statistical distribution of the four dynamers is strongly modified by addition of the cations, leading to an enforced distribution that displays a strong upregulation of P3, which binds Na, and the simultaneous increase of its agonist P4, whereas the antagonists P2 and P3 are strongly downregulated...

Jyh-ShingRJ (1993) ANFIS adaptive-network-based fuzzy inference system. IEEE Trans Syst Man Cybem... 

Neuro fuzzy modeling is a useful technique that combines the advantages of neural networks and fuzzy inference systems. In this approach, the fuzzy model is architecturally the same as a neural network. In this case one could use, for example error back-propagation to train the network to find the parameters of the fuzzy model. The most well-known method is the so-called ANFIS method the Adaptive-Network based Fuzzy Inference System. The method will be explained in this chapter and several examples will be developed as an illustration. 

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