Prospects of Development of the Oil Industry in the Global Economy and in the Regional Economies

Anisimov, Valery; Truntsevsky, Yuri; Bessel, V.V.; Yessetova, Saltanat

doi:10.32479/ijeep.8589

Cited by 5 publications

(6 citation statements)

References 6 publications

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“…Its bottom layer is composed of multiple restricted Boltzmann machines, each of which is trained separately. The top layer is a BP neural network [ 3 , 11 ]. The bottom Boltzmann machine is trained by unsupervised learning, and the top BP neural network is trained by supervised learning.…”

Section: Relevant Theories Of In-depth Learningmentioning

confidence: 99%

“…In the 1960s, when Hube and Wiesel studied cat visual cortex cells, they found that their neurons have a unique network structure and then proposed the concept of receptive field. In the 1980s, Fukushima proposed the neurocognitive machine model based on the inspiration of the wild theory [ 11 ]. Neurocognitive machines are also considered early convolutional neural networks.…”

Section: Relevant Theories Of In-depth Learningmentioning

confidence: 99%

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Construction of Prediction Model of Ecological Forestry Economic Development Trend Based on Deep Belief Network

Cao

2022

Computational Intelligence and Neuroscience

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With the rapid development of economy, environmental problems become more and more serious, and people begin to pay attention to ecological construction. Forestry is an important industry related to the long-term survival and development of mankind. It undertakes the important tasks of forest product supply and ecological construction. Therefore, the quality of its development has a direct impact on all aspects of ecological economic construction. It is related to China’s ecological construction and sustainable development and plays an important role in social development. The corresponding evaluation index system and evaluation model were established to deeply analyze the economic development trend of ecological forestry system. It has certain guiding significance to provide theoretical guidance for the future development direction of ecological forestry.

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Section: Relevant Theories Of In-depth Learningmentioning

confidence: 99%

Section: Relevant Theories Of In-depth Learningmentioning

confidence: 99%

Construction of Prediction Model of Ecological Forestry Economic Development Trend Based on Deep Belief Network

Cao

2022

Computational Intelligence and Neuroscience

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“…The issues of business efficiency in the context of energy transition are in the field of scientific discussion, but most of the work explores the strategies of energy companies aimed at their "greening" [9], the economic feasibility of developing promising technologies [10], and low-carbon fuel production plants [11]. There are a number of papers that emphasize the idea of the need to make changes in general approaches to evaluating effectiveness [12,13]. Certain tensions and uncertainties caused do not negate the impact of the global trend of decarbonization and the need to take them into account.…”

Section: Introductionmentioning

confidence: 99%

The Need for the Green Economy Factors in Assessing the Development and Growth of Russian Raw Materials Companies

Ulanov

2024

JCBAR

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Approaches to assessing economic development and growth in the context of transition to a green and low-carbon economy are considered on the example of the Russian raw materials business. The implementation of carbon regulation leads not only to the expected environmental results, but also to a change in market conditions. With the spread of protectionist measures and restrictions, the assessment of the former integral indicator is distorted. It is shown that the curtailment of long-term contracts for the supply of fossil fuels and restrictions on investments in traditional energy projects adjust the assessment. In this article, its author drew attention to the need to take into account the factors of the green economy in the context of the development and growth of Russian developing companies. Indices, ratings, as well as such indicator systems as ESG may be of interest as a criterion of success. One of the factors of sustainable development and growth of raw materials companies is the number of proven reserves of recoverable resources, the potential of hard-to-recover resource and the inability to reproduce natural resources. Based on the analysis of dependencies, it is proposed to develop strategies, which allow us to identify new opportunities. The system for assessing economic development and economic growth of raw materials and energy companies, built on a single-criterion approach, should consider the conditions of subsurface use, the level of reserves, and use additional indicators to consider the impact of external circumstances. The assessment of the Russian raw materials and energy business on market principles may show negative dynamics in the short term, but in the long term, expectations are optimistic. This situation is largely explained by the inconsistency of the set goals for climate protection and the delay or inadequacy of actions taken as an example.

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“…e advent of the sequencing of sequential learning (Seq2Seq), in recent years, offers a more versatile and extensible temporal modelling system. e seq2seq model, however, suffers from the possible issue of the need to compact all historical data into an internal constant length vector [7]. is may restrict the seq2seq model's ability to manage long sequences.…”

Section: Introductionmentioning

confidence: 99%

“…is may restrict the seq2seq model's ability to manage long sequences. Methods for resolving basic Seq2Seq shortcomings and skills in modelling long-range dependencies, such as regional economic structures of longrange processes in the general environment, are therefore proposed for attention mechanisms [7].…”

Section: Introductionmentioning

confidence: 99%

Regional Economy Using Hybrid Sequence‐to‐Sequence‐Based Deep Learning Approach

Peng

2022

Complexity

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In recent times, the role of the regional economy changed significantly under certain conditions of globalization and structural adjustment. The process of changing must be crucial to analyse regional economy and develop the planning of regional economy. Developing economies depend often on industries and country policies. Modern studies tend to participate in important factors in this field such as energy intensity, labour skills, local industries, resources, and local expertise. Furthermore, in this study, to start developing the regional economy and make the revolution in this field to connect it with new technology, we train the deep learning algorithm of gathering factors to manage them perfectly and make a good prediction for the future economy. Hybrid sequence to sequence (seq2seq) algorithms of deep learning fed with previous information from past years and run the system to compare the predicted result data with current information to evaluate the method to be certified for the coming years.

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Prospects of Development of the Oil Industry in the Global Economy and in the Regional Economies

Cited by 5 publications

References 6 publications

Construction of Prediction Model of Ecological Forestry Economic Development Trend Based on Deep Belief Network

Construction of Prediction Model of Ecological Forestry Economic Development Trend Based on Deep Belief Network

The Need for the Green Economy Factors in Assessing the Development and Growth of Russian Raw Materials Companies

Regional Economy Using Hybrid Sequence‐to‐Sequence‐Based Deep Learning Approach

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