Quality monitoring and fault detection are essential parts in automated electronics manufacturing systems. Information about process conditions enables operations to improve quality and increase throughput. This report presents a general quality monitoring framework and method for a manufacturing system. Proposed monitoring approach is an integration of model-based methods with systematically c...

Fuzzy rule based systems provide a framework for representing & processing information in a way that resembles human communication & reasoning process. Two approaches can be found in the literature which is used for rule based generation; In Knowledge Driven Models the requisite rule base is provide by domain expert & knowledge engineers. In the Data Driven Models the rule base is generated fro...

allows the user to define rules on contraindication alerts, drug interaction warnings, diagnostic and In the near future, every medical intreatment recommendations, etc. formation system wiil be equipped with a function that provides knowledge-based decision support. Data-driven knowledgebased decision support consists, in the first place, of a medical data-to-concept conversion step and, secon...

ABsTRAcT This chapter describes how to integrate medical knowledge with purely inductive (data-driven) methods for the creation of clinical prediction rules. It addresses three issues: representation of medical knowledge , secondary analysis of medical data, and evaluation of automatically induced predictive models in the context of existing knowledge. To address the complexity of the domain kn...

In this paper, a novel fuzzy rule transfer mechanism for self-constructing neural fuzzy inference networks is being proposed. The features of the proposed method, termed data-driven neural fuzzy system with collaborative fuzzy clustering mechanism (DDNFS-CFCM) are; (1) Fuzzy rules are generated facilely by fuzzy c-means (FCM) and then adapted by the preprocessed collaborative fuzzy clustering (...

Size-dependent longitudinal and torsional vibrations of nano-beams are examined by two-phase mixture integral elasticity. A new and efficient elastodynamic model is conceived by convexly combining the local phase with strain- and stress-driven purely nonlocal phases. The proposed stress-driven nonlocal integral mixture leads to well-posed structural problems for any value of the scale parameter...

in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

runoff simulation is a vital issue in water resource planning and management. various models with different levels of accuracy and precision are developed for this purpose considering various prediction time scales. in this paper, two models of ihacres (identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data) and ann (artificial neural network) mode...