Purpose The purpose of this paper is to predict the daily accuracy improvement for the Jakarta Islamic Index (JKII) prices using deep learning (DL) with small and big data of symmetric volatility information. Design/methodology/approach This paper uses the nonlinear autoregressive exogenous...

The VR/AR Industrial Coalition is a key initiative within the European Commissions' Audiovisual Media Action Plan launched in December 2020, aiming to boost the performance of this industry in Europe and support its optimal deployment. Here are the main takeaways, check the full paper for more...

Steigende Herausforderungen, wie z.B. ein intensiver Wettbewerbsdruck hinsichtlich Innovationen und eine damit einhergehende Individualisierung der Produkte sowie eine steigende Internationalisierung führen zu einem Wandel in der Automobilbranche. Die Kombination der Faktoren führt zu einem...

The price volatility of energy assets such as natural gas, crude oil, and coal among others do influence electricity prices, which altogether directly have significant economic impacts on different sectors of the economy. From this viewpoint, accurate energy price volatility predictions are very...

In the world of business, firms have started adopting technologies to develop and grow their businesses. To sustain in this competitive market there is a dire need for better performance and precision in prediction .To achieve this goal various businesses, require to accurately analyze and...

This study investigates the effectiveness of technology models in credit risk scoring modeling in emerging markets. the study proposes evaluation methods for credit risk scoring modeling for current and potential borrowers through an investigation into the Egyptian banking industry by offering...

This study describes accurate, computationally efficient models that can be implemented using IoT sensors for practical use in predicting frost events for point-scale agricultural applications. Frost damage in agriculture is a costly burden to farmers and global food security alike. Timely...

Power generation from the Sun is dominated by photovoltaics (PVs) whose efficiencies are severely limited by overheating due to the underutilization of the solar spectrum. Thermoelectric generators (TEGs) are used to reduce the overheating of PVs by forming hybrid PV-TEs capable of utilizing the...

With the advances in time-series prediction, several recent developments in machine learning have shown that integrating prediction methods into portfolio selection is a great opportunity. In this paper, we propose a novel approach to portfolio formation strategy based on a hybrid machine...