AIMC Topic: Gross Domestic Product

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A comprehensive analysis of key factors' impact on environmental performance: Evidence from Globe by novel super learner algorithm.

Journal of environmental management
This study aims to analyze comprehensively the impact of different economic and demographic factors, which affect economic development, on environmental performance. In this context, the study considers the Environmental Performance Index as the resp...

Regional economic forecast using Elman neural networks with wavelet function.

PloS one
Recently, the economy in Guangdong province has ranked first in the country, maintaining a good growth momentum. The prediction of Gross Domestic Product (GDP) for Guangdong province is an important issue. Through predicting the GDP, it is possible t...

Modelling the GDP of KSA using linear and non-linear NNAR and hybrid stochastic time series models.

PloS one
BACKGROUND: Gross domestic product (GDP) serves as a crucial economic indicator for measuring a country's economic growth, exhibiting both linear and non-linear trends. This study aims to analyze and propose an efficient and accurate time series appr...

China's GDP forecasting using Long Short Term Memory Recurrent Neural Network and Hidden Markov Model.

PloS one
This paper presents a Long Short Term Memory Recurrent Neural Network and Hidden Markov Model (LSTM-HMM) to predict China's Gross Domestic Product (GDP) fluctuation state within a rolling time window. We compare the predictive power of LSTM-HMM with ...

A Study on Regional GDP Forecasting Analysis Based on Radial Basis Function Neural Network with Genetic Algorithm (RBFNN-GA) for Shandong Economy.

Computational intelligence and neuroscience
Gross domestic product (GDP) is an important indicator for determining a country's or region's economic status and development level, and it is closely linked to inflation, unemployment, and economic growth rates. These basic indicators can comprehen...

Macroeconomic Image Analysis and GDP Prediction Based on the Genetic Algorithm Radial Basis Function Neural Network (RBFNN-GA).

Computational intelligence and neuroscience
The prediction of gross domestic product (GDP) is a research hotspot, and its importance is self-evident. Its complex internal change mechanism also increases the difficulty of analyzing GDP data. The genetic algorithm (GA) is applied to the paramete...

Assessing a fossil fuels externality with a new neural networks and image optimisation algorithm: the case of atmospheric pollutants as confounders to COVID-19 lethality.

Epidemiology and infection
This paper demonstrates how the combustion of fossil fuels for transport purpose might cause health implications. Based on an original case study [i.e. the Hubei province in China, the epicentre of the coronavirus disease-2019 (COVID-19) pandemic], w...

Research on the evolution and driving forces of the manufacturing industry during the "13th five-year plan" period in Jiangsu province of China based on natural language processing.

PloS one
The development of China's manufacturing industry has received global attention. However, research on the distribution pattern, changes, and driving forces of the manufacturing industry has been limited by the accessibility of data. This study propos...

A hybrid novel SVM model for predicting CO emissions using Multiobjective Seagull Optimization.

Environmental science and pollution research international
The agricultural sector is one of the most important sources of CO emissions. Thus, the current study predicted CO emissions based on data from the agricultural sectors of 25 provinces in Iran. The gross domestic product (GDP), the square of the GDP ...

Prediction of municipal solid waste generation using nonlinear autoregressive network.

Environmental monitoring and assessment
Most of the developing countries have solid waste management problems. Solid waste strategic planning requires accurate prediction of the quality and quantity of the generated waste. In developing countries, such as Malaysia, the solid waste generati...