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This chapter has the objective of presenting four studies involving neural networks in the area of advanced oxidative process. Advanced Oxidative Processes area based on the generation and reaction of hydroxyl radicals. Because they are not selective and it possesses a high oxidizing power are able to degrade organic contaminants. Mathematical modeling of chemical process is often addressed in photocatalytic function of some parameters that are inherent in the process, such as the geometry of a reactor or characteristics of the compound to be worked, such as solubility and spectral characteristics of organic compounds. By moving the geometry of the reactor, moves through the proposed model. When they moved the reagents, changes completely the kinetics of the reactions involved and consequently the reactor performance. The process of decolorization and degradation of organic compounds may involve, according to criteria adopted modeling, a series of reactions kinetics. The photocatalytic process modeling involves the solution to a complex set of equations of energy (radiation), the mass balance, momentum and heat, being a difficult process description. The performance of a photoreactor is strongly influenced by many physical-chemical interaction occurring between these variables. Conventional modeling techniques can produce models not appropriate. This sense, neural modeling, empirical, presents itself as alternative to the traditional model, because it is based on mathematical equation. Based on the study of behavioral characteristics of the sets of input and output of the process of discoloration and degradation of organic compounds, possessing the ability to "learn" the behavior of linear or nonlinear experimental data. Through this "learning" may provide the optimization of the action of hydroxyl radical oxidation. Are presented four applications involving neural networks modeling. a. Neural approximation of the reduction of cod effluents from the manufacturing of polyesters trought photo-fenton procces/ ozonization b. Hybrid neural model for decoloration by UV/ H2O2 involving process variables and structural parameters characteristics to azo dyes

Applications of Neural Networks in Advanced Oxidative Process