This is the second volume of the Advances in Data Warehousing and Mining (ADWM) book series. ADWM publishes books in the areas of data warehousing and mining. The topic of this volume is data mining and knowledge discovery. This volume consists of 14 chapters in four section, contributed by authors and editorial board members from the International Journal of Data Warehousing and Mining, as wel...

Model-free control” and the corresponding “intelligent” PID controllers (iPIDs), which already had many successful concrete applications, are presented here for the first time in an unified manner, where the new advances are taken into account. The basics of model-free control is now employing some old functional analysis and some elementary differential algebra. The estimation techniques becom...

State of the art deep reinforcement learning algorithms take many millions of interactions to attain human-level performance. Humans, on the other hand, can very quickly exploit highly rewarding nuances of an environment upon first discovery. In the brain, such rapid learning is thought to depend on the hippocampus and its capacity for episodic memory. Here we investigate whether a simple model...

This paper introduces methods for computing impulse response functions that do not require specification and estimation of the unknown dynamic multivariate system itself. The central idea behind these methods is to estimate flexible local projections at each period of interest rather than extrapolating into increasingly distant horizons from a given model, as it is usually done in vector autore...

The aim of this study is to investigate the effects of corporate governance mechanisms in preventing the bankruptcy of companies listed in Tehran Stock Exchange. For this purpose, corporate governance mechanisms, including institutional ownership, non-executive members of the board, CEO dual responsibility and free float stock are determined as independent variables and Bankruptcy based on the ...

In recent work [1], we introduced a new, linear-programming based method, for detecting underground features based on gravity measurements. The current paper takes this method one important step further, in that it makes it work under realistic conditions, where most of the physical characteristics of the environment are not known. In particular, the ADCS algorithm we introduce works when the f...

We " explain " , using a Classical approach, how the Universe was created out of " nothing " ,i.e., with no input of initial energy nor mass. The inflationary phase, with exponential expansion, is accounted for, automatically , by our equation of state for the very early Universe. This is a Universe with no-initial infinite singularity of energy density.

Model predictive control, MPC, is a model-based control philosophy that select control actions by on-line optimization of objective functions. Design methods based on MPC have found wide acceptance in industrial process control applications, and have been thoroughly studied by the academia. Most of the work so far have relied on linear models of different sophistication because of their advanta...

Simply put, reinforcement learning (RL) is a term used to indicate a large family of dierent algorithms RL that all share two key properties. First, the objective of RL is to learn appropriate behavior through trialand-error experience in a task. Second, in RL, the feedback available to the learning agent is restricted to a reward signal that indicates how well the agent is behaving, but does ...