This paper presents a comprehensive survey of web log/usage mining based on over 100
research papers. This is the first survey dedicated exclusively to web log/usage mining. The …

For a long time moving averages has been used for a financial data smoothing. It is one of
the first indicators in technical analysis trading. Many traders debated that one moving …

Smoothing time series allows removing noise. Moving averages are used in finance to
smooth stock price series and forecast trend direction. We propose optimised custom moving …

This paper investigates excitation information propagation in artificial societies. We use a
cellular automaton approach, in which it is assumed that social media is composed of tens of …

It is common practice to employ returns, price differences or log returns for financial risk
estimation and time series forecasting. In De Prado’s 2018 book, it was argued that by using …

In this paper two popular time series prediction methods–the Auto Regression Moving Average
(ARMA) and the multilayer perceptron (MLP)–are compared while forecasting seven real …

A novel loss function to train a net of K single-layer perceptrons (KSLPs) is suggested, where
pairwise misclassification cost matrix can be incorporated directly. The complexity of the …

We analyse reinforcement learning algorithms for self balancing robot problem. This is the
inverted pendulum principle of balancing robots. Various algorithms and their training …

The Efficient-Market Hypothesis (EMH) asserts that the market is efficient and whenever
new information comes up the market absorbs it by correcting itself. The corresponding …

Immunological principles can be used to build a sustainable investment portfolio. The theory
of immunology states that information about recognized pathogens is stored in the memory …