Neural computing technologies

Here, the key neural computing technologies and their application to formulation and formulation optimization are reviewed. 

RC Rowe, RJ Roberts. Artifical intelligence in pharmaceutical product formulation neural computing and emerging technologies. PSTT l(5) 200-205, 1998. 

Neural Computing a technology handbook for Professional II/plus users, NeuralWare Inc., Pittsburgh (USA) 1993... 

Developments in computer technology promoted the use of computationally demanding methods such as artificial neural networks, genetic algorithms, and multiway data analysis. 

This part of the book consists of one chapter (Chapter 1) to provide an overview of the domain field, genome informatics, with its major research areas and technologies a brief summary of the computational technology, artificial neural networks , and a summary of genome informatics applications. The latter two topics are further expanded into Part II, Neural Network Foundations, and Part III, Genome Informatics Applications. 

Recent advances in the technology of multisensor arrays and neural computing have made the development of the electronic nose of great interest to the food industry for discrimination between odors (26). Provided the instrument has been calibrated properly, the technique is rapid, nondestructive, and objective. Shen et al. (27) found the electronic nose was capable of measuring changes in volatile compounds associated with lipid oxidation in canola, com, and soybean oils stored under accelerated conditions and Aparicio et al. (28) found the electronic nose could be calibrated to detect rancidity levels in good quahty ohve oil spiked with rancid olive oil. 

Applications of neural computing in this field are as numerous as they are diverse and it is appropriate to review them based on the technology (or release rate controlling mechanism) used in the formulation of the product. 

Baan, 87, 88, 95, 492, 1738 BaanERP, 95, 304, 492 Backlogged demands, 1636—1637 Back propagation (BP), 163 Back-propagation neural nets, 1778-1779 Balanced scorecard, 321-322, 997-998 Balance (with introduction/use of computer technologies), 1228, 1229 Balance model of occupational safety and health, 1159-1162 Baldrige criteria, 1956—1957, 1964... 

Fan Yongjian, Mai Jianying, Shen Yanguang. 2009. Study of the Safety Assessment Model of Coal Mine Based on BP Neural Network. Intelligent Computation Technology and Automation International Conference 103—106. 

In addition, there is a need, which we acknowledge and are addressing, to develop a proper understanding of how and why the observed phenomena occur. Such an understanding will lead to a predictive science, a proper basis for a practical technology of neural computing. We need, for example, to be... 

A hands-on experience with the method is possible via the SPINUS web service [48. This service uses a client-server model. The user can draw a molecular structure within the web browser workspace (the client), and send it to a server where the predictions are computed by neural networks. The results are then sent back to the user in a few seconds and visualised with the same web browser. Several operations and different types of technology arc involved in the system ... 

Biocomputers. 2. Neural networks (computer science) 3. Information technology. 

This ability to express objectives in simple terms also allows fuzzy logic to be combined tightly with other technologies like neural networks to give neuro-fuzzy computing. As discussed below, this gives powerful data mining techniques that can be used in formulation. 

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