Intelligent Sensor Networks

Abstract

and other sources. His research expertise can be summarized as 3S-security, signals, and sensors: (1) security, which includes cyberphysical system security and medical security issues;(2) signals, which refers to intelligent signal processing, that is, using machine learning algorithms to process sensing signals; and (3) sensors, which includes wireless sensor network design issues.

An economic feasibility assessment framework for underutilised crops using Support Vector Machine

“…Insufficient data is often recognized as the main problem for poor and unreliable performance of machine learning and data mining techniques. This is due to the fact that collecting sufficiently large data could be costly and impossible in some cases (Fei Hu 2016). Studies on the impact of insufficient data with respect to training an inference engine for classification, regression and clustering have been carried out in different fields using different methods in Table 1.…”

Development of Machine Learning Models to Predict the Weld Defect Using Resistance Spot Welding Experimental Data

“…Using a different mathematical algorithm, a machine learning could develop a model using empirical machine data to analyze the pattern of the process. Compared to weld lobe curve, the ML model helps to predict the output of the process for a large range of parameters without utilizing many resources and time in the industry, which is useful for decision-making purposes [8]. However, implementing the machine learning methods in the manufacturing process, poses several challenges in terms of data quality and process complexity.…”