Academic Articles & Research Papers

Inflation impact of food prices: Case of Serbia

Food prices traditionally have an impact on inflation around the world. Movements in these prices are coming more from the supply side, then from the demand side. If treated as a supply shock, monetary policy should not react. However, food...

Gold Price Forecasting using Time Series Modeling on a Web Platform

Gold is one of the most favored investment instruments due to its stability and its ability to preserve value against inflation. However, its price movements are volatile and influenced by various global economic factors, currency exchange ...

Multi year changes of Aerosol Optical Depth in the monsoon region of the Indian Ocean since 1986 as seen in the AVHRR and TOMS data

Aerosol Optical Depth (AOD) data based on AVHRR and TOMS was analyzed to find out the changes in the Indian Ocean from 1981 to 2004. Four regions covering Indian Ocean north of 10° S were studied in detail. The results strongly sugge...

ZOTMPo–INAR(1) Process: Entropy and Modeling of Epidemiological Count Time Series Data

In this article, we propose a first-order integer-valued autoregressive (INAR(1)) model based on binomial thinning, in which the innovation sequence follows a zero–one–two-modified Poisson (ZOTMPo) distribution. The proposed model accommoda...

Superposed Epoch Analyses of Geoelectric Field Disturbances in Japan in Response to Different Geomagnetic Activities

Abstract An increase in geomagnetically induced currents (GICs) is an inevitable result of geomagnetic field disturbances, and is harmful to the power grid, in particular, at high latitudes. At mid and low latitudes, the amplitude of the GI...

Cybersecurity in the quantum era: Assessing the impact of quantum computing on infrastructure

The advent of quantum computing marks a transformative era in cybersecurity, challenging traditional cryptographic frameworks and broadening the horizons of computational capabilities. This paper navigates the transition to a quantum-resist...

Quantum computing for market research

The digital ecosystem continues to expand around the world and is revolutionising the way markets are researched. Indeed, consumer experiences are advertised and disseminated through so many channels and media that it has become a major cha...

The state of quantum computing applications in health and medicine

Abstract Quantum computing hardware and software have made enormous strides over the last years1. Questions around quantum computing’s impact on research and society have changed from “if” to “when/how”. The 2020s have been described as the...

Exploiting availability prediction in distributed systems

Loosely-coupled distributed systems have significant scale and cost advantages over more traditional architectures, but the availability of the nodes in these systems varies widely. Availability modeling is crucial for predicting per-machin...

Forecasting student achievement in MOOCs with natural language processing

Student intention and motivation are among the strongest predictors of persistence and completion in Massive Open Online Courses (MOOCs), but these factors are typically measured through fixed-response items that constrain student expressio...

Neural Networks in Business Forecasting

Neural Network is defined as the ability of a group to solve more problems than its individual members.The idea brings that a group of people can solve problems efficiently and offer greater insight and a better answer than any one individu...

Forecast combining with neural networks

This paper investigates the use of Artificial Neural Networks (ANNs) to combine time series forecasts of stock market volatility from the USA, Canada, Japan and the UK. We demonstrate that combining with nonlinear ANNs generally produces fo...

Neural Network Models for Time Series Forecasts

Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, time series forecasts produced by neural networks are compared with forecasts from six statistical time series ...

Neural Networks for Postprocessing Ensemble Weather Forecasts

Abstract Ensemble weather predictions require statistical postprocessing of systematic errors to obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished with distributional regression models in which the pa...

Artificial Neural Networks in Agriculture

Artificial neural networks are one of the most important elements of machine learning and artificial intelligence. They are inspired by the human brain structure and function as if they are based on interconnected nodes in which simple proc...

Neural networks for wave forecasting

Forecasting wind with neural networks

Neural networks in the capital markets

PART ONE: NEURAL NETWORKS: Introduction Design Considerations Methods for Optimal Network Design Data Modelling Considerations Testing Strategies and Metrics PART TWO: EQUITY APPLICATIONS: Modelling Stock Returns in the Framework of APT: A ...

Neural networks for financial forecasting

When applied to the world of finance, neural networks are automated trading systems, based on mapping inputs and outputs for forecasting probable future values. In Neural Networks for Financial Forecasting - the first book to focus on the r...

Recurrent Neural Networks

From the Publisher: With applications ranging from motion detection to financial forecasting, recurrent neural networks (RNNs) have emerged as an interesting and important part of neural network research. Recurrent Neural Networks: Design ...