Machine learning and intelligence science: IScIDE (C)

Stock Price Prediction using Machine Learning and Swarm Intelligence

Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...

Machine Learning and Citizen Science: Opportunities and Challenges of Human-Computer Interaction

Background and Aim: In processing large data, scientists have to perform the tedious task of analyzing hefty bulk of data. Machine learning techniques are a potential solution to this problem. In citizen science, human and artificial intelligence may be unified to facilitate this effort. Considering the ambiguities in machine performance and management of user-generated data, this paper aims to...

Working memory, fluid intelligence, and science learning

A review of the history of working memory (WM) studies finds that the concept of WM evolved from short-term memory to a multi-component system. Comparison between contemporary WM models reveals: (1) consensus that the content of WM includes not only task-relevant information, but also task-irrelevant information; (2) consensus that WM consists of phonological and visuospatial components; (3) co...

Developments in computational intelligence and machine learning

Publisher Rights Statement: NOTICE: this is the author’s version of a work that was accepted for publication in Neurocomputing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. ...

Next Generation Artificial Intelligence and Machine Learning