Nonlinear Trends in Modern Artificial Intelligence: A New Perspective

Benderskaya, Elena N.

doi:10.1007/978-3-642-34422-0_8

Cited by 7 publications

(3 citation statements)

References 29 publications

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“…Based on the background of artificial intelligence, some leaders, teachers, and students in colleges do not have a comprehensive understanding of AI translation technology. Teachers' insufficient use of AI technology and an imperfect curriculum evaluation system have also had negative effects on students' improvement of translation ability and mastery of translation methods [5]. Inadequate guidance from teachers is also an important factor in the effectiveness of students' learning.…”

Section: Introductionmentioning

confidence: 99%

IoT-Based English Translation Teaching from the Perspective of Artificial Intelligence

Liu

2022

International Journal of Antennas and Propagation

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In recent years, with the development of artificial intelligence, the Internet of Things (IoT) has become a research hotspot in industry and academia. At the same time, as a derivative tool of artificial intelligence, machine translation based on the IoT is constantly being applied to English translation and its teaching. In teaching, helping students learn English translation has been the focus of machine translation in recent years. Compared with human translation, machine translation is more efficient and convenient. However, machine translation also has some problems. Compared with traditional human translation, it cannot meet the requirements of faithfulness, expressiveness, and elegance of translation. In many fields, neural network translation is comparable to human translation. In the field of English translation teaching, neural network translation has broad prospects. With the gradual maturity of neural network translation, we should think about how to use neural network translation to make it a powerful English translation teaching tool instead of sticking to traditional teaching and cultivating students who are completely unable to compare it with neural network translation. Therefore, in the context of rapid AI iteration, college English translation teaching should also keep pace with the times. With the help of tools such as neural network translation, English translation talents who can skillfully use AI technology can be trained quickly and efficiently so that they can keep pace with the times and master the power of AI. The research in this paper provides important guidance for the application of artificial intelligence and the Internet of Things, especially for intelligent relaying.

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Section: Introductionmentioning

confidence: 99%

IoT-Based English Translation Teaching from the Perspective of Artificial Intelligence

Liu

2022

International Journal of Antennas and Propagation

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“…The outputs of meteorological models need to be downscaled to small-scale resolutions in the study region to reduce forecast errors. Recently, AI has been used for downscaling weather forecasts due to its ability to identify complex patterns and unforeseen behavior (Benderskaya, 2013), and its capability of extracting non-linear relations from data without prior knowledge of the parametric form of these relations (Valverde Ramírez et al, 2006). Here, we downscale the forecasts to the point-scale of synoptic weather stations, whose data are used to force the hydrological rainfall-runoff model.…”

Section: Ai Downscaling Methodsmentioning

confidence: 99%

Daily reservoir inflow forecasting using weather forecast downscaling and rainfall-runoff modeling: Application to Urmia Lake basin, Iran

Meydani

Dehghanipour

Schoups

et al. 2022

Journal of Hydrology: Regional Studies

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“…Further, it relates to certain tasks involving higher mental processes such as solving problems, classification, learning, building analogies, creativity, language processing, knowledge, etc. [8] discusses about the initial AI systems for problem solving and planning. This could be illustrated in one of the approaches called means-ends analysis, which is directly connected to human thoughts.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Technology and its Challenges-A Review

Abitha¹

2016

JECSE

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In the last two decades, researchers have found many advantages related to Artificial Intelligence (AI) in the performance of both service and manufacturing systems. It includes alternate methods to conventional techniques and there are mechanisms of integrated systems. Currently, many researches related to artificial intelligence are under process. At present, artificial intelligence has been used to solve various problems in several fields and has become more popular around the world. This field is extremely difficult to review either chronologically or thematically. AI has a long history of growing constantly and changing tremendously. Connected with the history of computers, artificial intelligence is the main concept behind the fifth generation computers. This review paper deals with the framework of artificial intelligence and focuses on fields related to artificial intelligence. Particularly this paper describes about the recent growth in the field of artificial intelligence and its applications. Several issues of artificial intelligence are analysed. It is concluded that still many researches are yet to be conducted for further growth in the field of Artificial Intelligence (AI).

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Nonlinear Trends in Modern Artificial Intelligence: A New Perspective

Cited by 7 publications

References 29 publications

IoT-Based English Translation Teaching from the Perspective of Artificial Intelligence

IoT-Based English Translation Teaching from the Perspective of Artificial Intelligence

Daily reservoir inflow forecasting using weather forecast downscaling and rainfall-runoff modeling: Application to Urmia Lake basin, Iran

Artificial Intelligence Technology and its Challenges-A Review

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