PARALLEL PROCESSING OF CHEMICAL INFORMATION IN A LOCAL AREA NETWORK-II. A PARALLEL CROSS-VALIDATION PROCEDURE FOR ARTIFICIAL NEURAL NETWORKS E. P. P. A DERKS,* M. L. M. BECKER& W. J. MELSSEN and L. M. C. BUYDENS
نویسندگان
چکیده
This paper describes a parallel cross-validation (PCV) procedure, for testing the predictive ability of multi-layer feed-forward (MLF) neural networks models, trained by the generalized delta learning rule. The PCV program has been parallelized to operate in a local area computer network. Development and execution of the parallel application was aided by the HYDRA programming environment, which is extensively described in Part I of this paper. A brief theoretical introduction on MLF networks is given and the problems, associated with the validation of predictive abilities, will be discussed. Furthermore, this paper comprises a general outline of the PCV program. Finally, the parallel PCV application is used to validate the predictive ability of an MLF network modeling a chemical non-linear function approximation problem which is described extensively in the literature. Copyright
منابع مشابه
Parallel Processing of Chemical Information in a Local Area Network - I. Hydra: Concept, Configuration, and Implementation of Parallel Applications
Sophisticated software packages put an increasing demand on computer hardware. In local area networks, computational intensive programs can lower the performance of individual workstations to an unacceptable level. However, utilizing in a coarse grained sense the computing power of all hosts in such networks, offers the potential to achieve considerable improvements in execution speed within re...
متن کاملUsing artificial neural networks for solving chemical problems Part I. Multi-layer feed-forward networks
متن کامل
Parallel Processing of Chemical Information in a Local Area Network - III. Using Genetic Algorithms for Conformational Analysis of Biomacromolecules
Multi-dimensional nuclear magnetic resonance experiments are an excellent means of revealing the three-dimensional structure of biomacromolecules in solution. However, the search space in the conformational analysis of biomacromolecules, using multi-dimensional NMR data, is huge and complex. This calls for global optimization techniques with good sampling properties. This paper describes a gene...
متن کاملAn improved structure models to explain retention behavior of atmospheric nanoparticles
The quantitative structure-retention relationship (QSRR) of nanoparticles in roadside atmosphere against the comprehensive two-dimensional gas chromatography which was coupled to high-resolution time-of-flight mass spectrometry was studied. The genetic algorithm (GA) was employed to select the variables that resulted in the best-fitted models. After the variables were selected, the linear multi...
متن کاملApplication of Artificial Neural Networks (ANN) and Image Processing for Prediction of Gravimetrical Properties of Roasted Pistachio Nuts and Kernels
Roasting is among the most common methods of nut processing causing physical and chemical changes and ultimately increasing overall acceptance of the product. In this research, the effects of temperature (90, 120 ,and 150°C), time (20, 35 ,and 50 min) ,and roasting air velocity (0.5, 1.5 ,and 2.5 m/s) on gravimetrical properties of pistachio nuts and kernels including unit mass, true density, o...
متن کامل