In this competitive world, the supervision and monitoring of human resources are primary
and necessary tasks to drive context-aware applications. Advancement in sensor and …

Transfer learning aims to provide a framework to utilize previously-acquired knowledge to
solve new but similar problems much more quickly and effectively. In contrast to classical …

This paper intends to provide an overview on recent development of knowledge transfer for
rotary machine fault diagnosis (RMFD) by using different transfer learning techniques. After …

Traditional optimization solvers tend to start the search from scratch by assuming zero prior
knowledge about the task at hand. Generally speaking, the capabilities of solvers do not …

Production optimization led by computing intelligence can greatly improve oilfield economic
effectiveness. However, it is confronted with huge computational challenge because of the …

In most real-world settings, designs are often gradually adapted and improved over time.
Consequently, there exists knowledge from distinct (but possibly related) design exercises …

This paper draws motivation from the remarkable ability of humans to extract useful building-
blocks of knowledge from past experiences and spontaneously reuse them for new and …

With the recent influx of electric vehicles and other electrical consumer products, the market
has created a large demand for lithium-ion batteries, however, the non-linearity of their …

To solve travelling salesman problems (TSPs), most existing evolutionary algorithms search
for optimal solutions from zero initial information without taking advantage of the historical …

Genetic programming (GP) is a well-known evolutionary computation technique, which has
been successfully used to solve various problems, such as optimization, image analysis …