The use of multi-criteria decision-making methods in business analytics: A comprehensive literature review
Business analytics (BA) systems are considered significant investments for enterprises
because they have the potential to considerably improve firms' performance. With the value …
because they have the potential to considerably improve firms' performance. With the value …
Evolutionary dynamic multi-objective optimisation: A survey
Evolutionary dynamic multi-objective optimisation (EDMO) is a relatively young but rapidly
growing area of investigation. EDMO employs evolutionary approaches to handle multi …
growing area of investigation. EDMO employs evolutionary approaches to handle multi …
The state of the art and taxonomy of big data analytics: view from new big data framework
Big data has become a significant research area due to the birth of enormous data
generated from various sources like social media, internet of things and multimedia …
generated from various sources like social media, internet of things and multimedia …
A hybrid multi-resolution multi-objective ensemble model and its application for forecasting of daily PM2. 5 concentrations
PM2. 5 concentrations forecasting can provide early air pollution warning information for the
public in advance. In this study, a novel multi-resolution ensemble model for multi-step PM2 …
public in advance. In this study, a novel multi-resolution ensemble model for multi-step PM2 …
Semantic similarity controllers: On the trade-off between accuracy and interpretability
J Martinez-Gil, JM Chaves-Gonzalez - Knowledge-Based Systems, 2021 - Elsevier
In recent times, we have seen an explosion in the number of new solutions to address the
problem of semantic similarity. In this context, solutions of a neuronal nature seem to obtain …
problem of semantic similarity. In this context, solutions of a neuronal nature seem to obtain …
BIGOWL: Knowledge centered big data analytics
C Barba-González, J García-Nieto… - Expert Systems with …, 2019 - Elsevier
Abstract Knowledge extraction and incorporation is currently considered to be beneficial for
efficient Big Data analytics. Knowledge can take part in workflow design, constraint …
efficient Big Data analytics. Knowledge can take part in workflow design, constraint …
Corrected multi-resolution ensemble model for wind power forecasting with real-time decomposition and Bivariate Kernel density estimation
The power integration is a challenge for the power system because of the fluctuation of the
wind power. Wind power forecasting can estimate the future fluctuation of the wind power …
wind power. Wind power forecasting can estimate the future fluctuation of the wind power …
InDM2: Interactive dynamic multi-objective decision making using evolutionary algorithms
Dynamic optimization problems involving two or more conflicting objectives appear in many
real-world scenarios, and more cases are expected to appear in the near future with the …
real-world scenarios, and more cases are expected to appear in the near future with the …
An improved query optimization process in big data using ACO-GA algorithm and HDFS map reduce technique
Storing as well as retrieving the data on a specific time frame is fundamental for any
application today. So an efficiently designed query permits the user to get results in the …
application today. So an efficiently designed query permits the user to get results in the …
Multi-objective big data optimization with jmetal and spark
Abstract Big Data Optimization is the term used to refer to optimization problems which have
to manage very large amounts of data. In this paper, we focus on the parallelization of …
to manage very large amounts of data. In this paper, we focus on the parallelization of …