مقاله انگلیسی رایگان در مورد هوش مصنوعی و یادگیری ماشین در سیستم انرژی – الزویر 2023

 

مشخصات مقاله
ترجمه عنوان مقاله هوش مصنوعی و یادگیری ماشین در سیستم های انرژی: دیدگاه کتابشناختی
عنوان انگلیسی مقاله Artificial intelligence and machine learning in energy systems: A bibliographic perspective
نشریه الزویر
انتشار مقاله سال 2023
تعداد صفحات مقاله انگلیسی 18 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
نوع نگارش مقاله
مقاله مروری (Review Article)
مقاله بیس این مقاله بیس نمیباشد
نمایه (index) JCR – Master Journal List – Scopus – DOAJ
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
10.660 در سال 2020
شاخص H_index 43 در سال 2022
شاخص SJR 2.254 در سال 2020
شناسه ISSN 2211-467X
شاخص Quartile (چارک) Q1 در سال 2020
فرضیه ندارد
مدل مفهومی ندارد
پرسشنامه ندارد
متغیر ندارد
رفرنس دارد
رشته های مرتبط مهندسی کامپیوتر – مهندسی انرژی
گرایش های مرتبط هوش مصنوعی – سیستم های انرژی – فناوری انرژی
نوع ارائه مقاله
ژورنال
مجله  بررسی استراتژی انرژی – Energy Strategy Reviews
دانشگاه Faculty of New Science and Technologies, University of Tehran, Tehran, Iran
کلمات کلیدی هوش مصنوعی – یادگیری ماشین – سیستم های انرژی – تحقیق کتابشناختی
کلمات کلیدی انگلیسی Artificial intelligence – Machine learning – Energy systems – Bibliographic research
شناسه دیجیتال – doi
https://doi.org/10.1016/j.esr.2022.101017
لینک سایت مرجع https://www.sciencedirect.com/science/article/pii/S2211467X22002115
کد محصول e17341
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
1 Introduction
2 Common machine learning methods and approaches
3 Methodology
4 Results and discussion
5 Conclusion
Declaration of competing interest
Data availability
References

بخشی از متن مقاله:

Abstract

     Economic development and the comfort-loving nature of human beings in recent years have resulted in increased energy demand. Since energy resources are scarce and should be preserved for future generations, optimizing energy systems is ideal. Still, due to the complexity of integrated energy systems, such a feat is by no means easy. Here is where computer-aided decision-making can be very game-changing in determining the optimum point for supply and demand. The concept of artificial intelligence (AI) and machine learning (ML) was born in the twentieth century to enable computers to simulate humans’ learning and decision-making capabilities. Since then, data mining and artificial intelligence have become increasingly essential areas in many different research fields. Naturally, the energy section is one area where artificial intelligence and machine learning can be very beneficial. This paper uses the VOSviewer software to investigate and review the usage of artificial intelligence and machine learning in the energy field and proposes promising yet neglected or unexplored areas in which these concepts can be used. To achieve this, the 2000 most recent papers in addition to the 2000 most cited ones in different energy-related keywords were studied and their relationship to AI- and ML-related keywords was visualized. The results revealed different research trends in recent years from the basic to more cutting-edge topics and revealed many promising areas that are yet to be explored. Results also showed that from the commercial aspect, patents submitted for artificial intelligence and machine learning in energy-related areas had a sharp increase.

Introduction

     Economic development and increasing welfare are always entangled with the rising consumption of energy resources. Increasing energy generation as the default answer to how to cope with this additive energy consumption may not be the best answer. From an energy justice perspective, it’s not acceptable to deplete energy reservoirs that belong to the next generations [1]. Although retrofitting existing equipment and minimizing energy usage by combining (or cascading) multiple systems for increased efficiency may be an answer to this challenge, increasing efficiency may not be the ideal solution. It’s valid that efficiency leads to lower consumption, but it should be noted that many of these systems might also be able to be turned off or operate on lower loads. So, a more dynamic approach may be a better solution.

     Artificial intelligence and machine learning are relatively new concepts in energy that can be promising tools to operate systems by implementing past and predicted futures to increase the effectiveness of systems.

Conclusion

     The concept of artificial intelligence (AI) and machine learning (ML) is for computers to simulate humans’ learning and decision-making capabilities. With advances in computing systems, AI and ML have become increasingly important areas in many different branches of science and industry. The energy section is also one of the areas that can benefit from AI and ML. To investigate the current standing point of AI and ML in energy-related areas, we used VOSviewer software to investigate and review the relatively new usage of AI and ML in the energy field and propose promising or neglected areas in which these concepts can be used.

     The results showed that from 2000 AI gains an increasing focus, especially after 2014 when the number of articles in ML skyrocketed. And in 6 years become 10 times more compared to 2014. Although there have been many papers in different fields of energy that introduced new usages of AI and ML in that section, due to the vastness of energy usage and respected fields of it, obviously, in no way the available articles could cover all these areas.

2 دیدگاه

  1. سلام من میخوام این مقاله رو ترجمه کنم ایا دستمزدی برا من داره یانه

    1. سلام، برای این مورد با پشتیبانی سایت ای ترجمه تماس بگیرید. با تشکر
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