A Neuro-fuzzy-stochastic frontier analysis approach for long-term natural gas consumption forecasting and behavior analysis: The cases of Bahrain, Saudi Arabia, Syria, and UAE

2011 ◽  
Vol 88 (11) ◽  
pp. 3850-3859 ◽  
Author(s):  
A. Azadeh ◽  
S.M. Asadzadeh ◽  
M. Saberi ◽  
V. Nadimi ◽  
A. Tajvidi ◽  
...  
Keyword(s):  
Saudi Arabia ◽  
Natural Gas ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Frontier Analysis ◽  
Neuro Fuzzy ◽  
Gas Consumption ◽  
Natural Gas Consumption ◽  
And Behavior

scholarly journals Long-Term Natural Gas Consumption Forecasting Based on Analog Method and Fuzzy Decision Tree

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4905
Author(s):  
Bartłomiej Gaweł ◽  
Andrzej Paliński
Keyword(s):  
Natural Gas ◽  
Decision Trees ◽  
Energy Intensity ◽  
Fuzzy Decision ◽  
Energy Mix ◽  
Starting Point ◽  
Gas Consumption ◽  
Natural Gas Consumption ◽  
Fuzzy Decision Trees

Classic forecasting methods of natural gas consumption extrapolate trends from the past to subsequent periods of time. The paper presents a different approach that uses analogues to create long-term forecasts of the annual natural gas consumption. The energy intensity (energy consumption per dollar of Gross Domestic Product—GDP) and gas share in energy mix in some countries, usually more developed, are the starting point for forecasts of other countries in the later period. The novelty of the approach arises in the use of cluster analysis to create similar groups of countries and periods based on two indicators: energy intensity of GDP and share of natural gas consumption in the energy mix, and then the use of fuzzy decision trees for classifying countries in different years into clusters based on several other economic indicators. The final long-term forecasts are obtained with the use of fuzzy decision trees by combining the forecasts for different fuzzy sets made by the method of relative chain increments. The forecast accuracy of our method is higher than that of other benchmark methods. The proposed method may be an excellent tool for forecasting long-term territorial natural gas consumption for any administrative unit.

scholarly journals Forecasting of Day-Ahead Natural Gas Consumption Demand in Greece Using Adaptive Neuro-Fuzzy Inference System

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2317 ◽  
Author(s):  
Konstantinos Papageorgiou ◽  
Elpiniki I. Papageorgiou ◽  
Katarzyna Poczeta ◽  
Dionysis Bochtis ◽  
George Stamoulis
Keyword(s):  
Neural Networks ◽  
Natural Gas ◽  
Fuzzy Inference ◽  
Inference System ◽  
Hybrid Combination ◽  
Neuro Fuzzy ◽  
Gas Consumption ◽  
Natural Gas Consumption ◽  
Natural Gas Demand ◽  
Consumption Demand

(1) Background: Forecasting of energy consumption demand is a crucial task linked directly with the economy of every country all over the world. Accurate natural gas consumption forecasting allows policy makers to formulate natural gas supply planning and apply the right strategic policies in this direction. In order to develop a real accurate natural gas (NG) prediction model for Greece, we examine the application of neuro-fuzzy models, which have recently shown significant contribution in the energy domain. (2) Methods: The adaptive neuro-fuzzy inference system (ANFIS) is a flexible and easy to use modeling method in the area of soft computing, integrating both neural networks and fuzzy logic principles. The present study aims to develop a proper ANFIS architecture for time series modeling and prediction of day-ahead natural gas demand. (3) Results: An efficient and fast ANFIS architecture is built based on neuro-fuzzy exploration performance for energy demand prediction using historical data of natural gas consumption, achieving a high prediction accuracy. The best performing ANFIS method is also compared with other well-known artificial neural networks (ANNs), soft computing methods such as fuzzy cognitive map (FCM) and their hybrid combination architectures for natural gas prediction, reported in the literature, to further assess its prediction performance. The conducted analysis reveals that the mean absolute percentage error (MAPE) of the proposed ANFIS architecture results is less than 20% in almost all the examined Greek cities, outperforming ANNs, FCMs and their hybrid combination; and (4) Conclusions: The produced results reveal an improved prediction efficacy of the proposed ANFIS-based approach for the examined natural gas case study in Greece, thus providing a fast and efficient tool for utterly accurate predictions of future short-term natural gas demand.

Exploring the long-term trade-off between efficiency and value creation in horizontal M&As

2018 ◽  
Vol 9 (2) ◽  
pp. 130-147 ◽  
Author(s):  
Mfon Nathaniel Udo Akpan ◽  
Nai Chiek Aik ◽  
Peter Fernandes Wanke ◽  
Wong Hong Chau
Keyword(s):  
Stochastic Frontier Analysis ◽  
Economic Value ◽  
Operating Performance ◽  
Stochastic Frontier ◽  
Value Added ◽  
Content Type ◽  
Frontier Analysis ◽  
Scale Size ◽  
Residual Income Valuation

Purpose The purpose of this paper is to investigate the voluntary horizontal M&A impact on operating performance in Nigeria between 1995 and 2012 under different complementary approaches. Design/methodology/approach Residual income valuation (RIV), economic value-added (EVA), data envelopment analysis (DEA) and stochastic frontier analysis (SFA). Findings Results showed a statistically significant improvement in the technical efficiency of both bidder and target companies, the reduced efficiency levels of the bidder firms under DEA scores reveals the specifics of the productive technology. This may suggest that resulting merged companies in Nigeria may have not even become too big in scale or even reached the most productive scale size, despite their almost monopolistic position in the sector. This happens because the scale size of the sector is small per se, implying that the investments necessary to achieve synergistic gains have to be partially covered by price increases. Practical implications This study will guide both the M&A practitioners, investment banks, and the policy makes. In terms of having to review M&A policy as well as seeing to the improvement in the infrastructural needs. Social implications With improved performance, employment can be created thereby giving employment to the youths. This will reduce social problems. Originality/value From the literature and records, no long-term operating performance on voluntary mergers and acquisitions has not been carried out in Nigeria. The paper seeks to know the fundamental value of the firms after these transactions with the current methodology that is acceptable from the literature.

scholarly journals Probing the Energy-Environmental Kuznets Curve Hypothesis in Oil and Natural Gas Consumption Models Considering Urbanization and Financial Development in Middle East Countries

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3178
Author(s):  
Haider Mahmood ◽  
Nabil Maalel ◽  
Muhammad Shahid Hassan
Keyword(s):  
Saudi Arabia ◽  
Natural Gas ◽  
Oil Consumption ◽  
Long Run ◽  
Negative Effect ◽  
Short Run ◽  
Oil And Natural Gas ◽  
Gas Consumption ◽  
Natural Gas Consumption ◽  
Positive Effect

Economic growth, urbanization, and financial market development (FMD) may increase energy demand in any economy. Non-renewable sources of energy consumption, i.e., oil consumption and natural gas consumption (NGC), could have environmental consequences. We examine the effects of economic growth, urbanization, and FMD on the oil consumption and NGC in Middle East countries using the period 1975–2019. In the panel results, we found a positive effect of income and a negative effect of income-squared on oil and natural gas consumption. Hence, we corroborate the existence of the environmental Kuznets curve (EKC) hypothesis in oil and natural gas consumption models of the Middle East region. Urbanization has a positive effect on oil and natural gas consumption. FMD has a positive effect on oil consumption and has a negative effect on NGC. From the long-run, country-specific results, we validate the existence of the EKC hypothesis in the oil consumption models of Iran and Iraq. The EKC is also found in the natural gas consumption models of Iran, Kuwait, and the UAE. From the short-run results, the EKC hypothesis is validated in the oil consumption models of Iran, Iraq, and Israel. The EKC is also corroborated in the NGC models of Iran, Kuwait, and the UAE. In the long run, urbanization has a positive effect on oil consumption in Iraq, Kuwait, Saudi Arabia, and Qatar. Further, urbanization has a positive effect on the NGC in Iraq, Israel, and Saudi Arabia. Conversely, urbanization has a negative effect on oil consumption in Israel. In the short run, urbanization has a positive effect on oil consumption in Iraq, Israel, Kuwait, and Qatar. Moreover, urbanization has a positive effect on the NGC in Iraq. On the other hand, urbanization has a negative effect on oil consumption in Saudi Arabia and Iran. In the long run, FMD has a positive effect on oil consumption in Saudi Arabia and Israel. In the short run, FMD has a positive effect on oil consumption in Israel, Kuwait, and Saudi Arabia. In contrast, FMD has a negative effect on oil consumption in the UAE. Moreover, a positive effect of FMD on NGC is found in the UAE. However, FMD has a negative effect on the NGC in Israel.

Short-term natural gas consumption forecasting from long-term data collection

Energy ◽  
2021 ◽  
Vol 218 ◽  
pp. 119430
Author(s):  
Radek Svoboda ◽  
Vojtech Kotik ◽  
Jan Platos
Keyword(s):  
Natural Gas ◽  
Data Collection ◽  
Short Term ◽  
Gas Consumption ◽  
Natural Gas Consumption ◽  
Term Data

scholarly journals Technical efficiency and its determinants for Czech livestock farms

2019 ◽  
Vol 65 (No. 4) ◽  
pp. 175-184 ◽  
Author(s):  
Vladimír Kostlivý ◽  
Zuzana Fuksová
Keyword(s):  
Organic Farming ◽  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Organic Farms ◽  
Conventional Agriculture ◽  
Frontier Analysis ◽  
Conventional Farms ◽  
Farm Accountancy Data Network

Organic farming has become an important part of Czech agriculture. The aim of this study is an evaluation of the technical efficiency of Czech organic farms and determining the main factors, including subsidies, which affect the technical efficiency of both conventional and organic farms. The Farm Accountancy Data Network Czech Republic (FADN CR) database provides sufficient panel data for this kind of research focusing on types of farming with livestock production. The methodological tool used to achieve the aim of this paper is the parametric stochastic frontier analysis, “True” Random Effects model, supposing farms heterogeneity and time variant determinants of inefficiency. The results of the research verified differences in the technical efficiency of organic and conventional agriculture related both to the different farming methods and to the production conditions. The type of farming and the economic size of farms influence the farms’ profitability, economic performance and comparability with conventional farms. The technical efficiency of organic farming is growing over the long term. Farms with growing technical efficiency show a decline in the proportion of operating subsidies to production, irrespective of their classification in quartiles by the technical efficiency estimate.

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