The focus of the work is maintained in the formal mathematical presentation and implementation of the data mining procedure and the controllability assessment of different solvents as well as in the use of rigorous process design models.
As traditional statistical methods are gradually being defeated by both the amount of data and the general absence of underlying hypotheses, data mining procedures are becoming increasingly popular and user-friendly.
Grid and high throughput computing model mining procedures based on neuro-fuzzy networks and genetic algorithms, generate: (i) collections of models composed of sets of time lag terms from the time series, and (ii) prediction functions represented by neuro-fuzzy networks.
In this study, we develop an expert system framework that utilizes text and data mining procedures for analyzing innovation through textual patent data.
Here we apply Factor Analysis (FA) [ 9], a multivariate tool related to PCA, coupled to clustering algorithms in sample space, t-test scores in gene space and data mining procedures.
The data mining procedures used for data preparation, modeling and simulation, which include statistics, methods of artificial intelligence and hybrid models in form of cascade committee machines, are described.
Moreover, the text mining procedures usually could provide several false positive associations and therefore those tools which also combine text-mining with other data sources in the analysis are preferred [ 8, 41].
Here we suggest that there is room for creative minds to imagine innovative ways to apply these techniques and to merge them with data mining procedures.
The DNA Microarray Integromics Analysis Platform supports a wide range of analyses, including primary raw data processing and detection of differential expression, as well as more advanced techniques, including data mining procedures explaining gene expression-phenotype relationships (clustering, multidimensional scaling, and construction of predictive models).
These results indicated that our mining and annotation strategy was reliable and distinguished its self from some previous mining procedures purely based on sequence analysis.
