Monkey Algorithm (MA) is a metaheuristic search algorithm. This article will describe the main components of the algorithm and present solutions for the ascent (upward movement), local jump and global jump. The algorithm was proposed by R. Zhao and W. Tang in 2007. The algorithm simulates the behavior of monkeys as they move and jump over mountains in search of food. It is assumed that the monkeys come from the fact that the higher the mountain, the more ...
The main advantage of relational models is the ability to build dependencies between objects. That enables the structuring of the source data. The relational model can be represented in the form of graphs, in which objects and events are represented as nodes, while relationships show dependencies between objects and events. more...
After reading this article, you will be able to detect highs and lows, identify trend types, double tops, and bottoms accordingly. more...
In our previous article, we discussed how equalizers in category theory can be employed to estimate volatility changes using sampled data. In this follow-up article, we will delve into composition and cones in category theory by exploring the significance of various cone setups on the end results of analysis. more...
Gravitational Search Algorithm (GSA) was proposed by E. Rashedi to solve the optimization problem, especially non-linear problems, following the principles of Newton's law of gravitation. In the proposed algorithm, particles are considered as objects and their performance is estimated taking into account their masses. more...
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