Random Walk Generation and Classification

The international arab journal of information technology

article

Afrah Mousa¹  Thorsten Auth²  Anas Samara³  Suhail Odeh³ 

[1] Department of Software Engineering Bethlehem University;Institution for Advanced Simulation Forschungszentrum Jülich;Departmen of Software Engineering Bethlehem University

关键词: Random walk;    machine learning;    experiential learning;   

DOI  :  10.34028/iajit/19/3A/14

学科分类：计算机科学（综合）

来源: Zarqa University

【 摘 要 】

Advancements in technology have introduced new approaches in teaching and learning processes. Machine learningalgorithms analyse and recognize patterns of data and subsequently become able to make reasonable decisions. In playingcomplex games, such as chess and go, machine learning algorithms have even already outperformed humans. This paperpresents a software platform ‘DiscimusRW’ that introduces a novel approach for teaching, learning, and researching randomwalk theory and getting hands-on experience in machine learning. Random walk theory represents the foundations of manyfundamental processes, including the diffusion of substances in solvents, epidemics’ spread, and financial markets’ development.‘DiscimusRW’ is composed of three main features: 1. Random walk generation using mathematical Equations, 2. Random walkclassification using supervised learning algorithms, and 3. Random walk visualization. A few users who explored ‘DiscimusRW’showed an interest and positive feedback that assured the experiential learning experience achieved using this software, whichwill therefore reinforce random walk teaching and learning.

【 授权许可】

Unknown