Application of a multiple linear regression and an artificial neural network model for the heating performance analysis and hourly prediction of a large-scale ground source heat pump system

Park, Sang Ku; Moon, Hyeun Jun; Min, Kyung Chon; Hwang, Chong-Sun; Kim, Suduk

doi:10.1016/j.enbuild.2018.01.029

Cited by 79 publications

(19 citation statements)

References 21 publications

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“…Neural Network [9]. The neuron in the artificial neural network is a biomimetic model established by taking the biological nerve cells as the imitation object.…”

Section: Learning Methods Based On Artificialmentioning

confidence: 99%

Data Analysis of Related Factors of Adolescent Physical Exercise Behavior Based upon Artificial Neural Network Model

Chen

Dai

Ren

2022

Wireless Communications and Mobile Computing

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Physical exercise behavior is to protect physical health through scientific physical activity (certain frequency, time, and intensity) in leisure time. The purpose of this paper is to study how to analyze and study the related factors of adolescent physical exercise behavior based on an artificial neural network model and describe the BP learning algorithm. This paper raises the question of the influencing factors of adolescents’ physical exercise behavior. This problem is based on an artificial neural network, so the paper expounds around the concept of artificial neural network and related algorithms and designs and analyzes relevant factors. The experimental results show that among the 4-17-year-old respondents, 45 students have the habit of physical exercise, accounting for 37.5% of the respondents in this age group. Among the 59 people with the habit of physical exercise in this survey, 41 people, accounting for 69.5%, believed that their interest in sports was greatly influenced by their surrounding classmates. There are 40 parents who have one parent who is college or above, accounting for 67.8% and other data. All of them show that the influencing factors of adolescents’ physical exercise behavior come from many aspects.

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“…Neural Network [9]. The neuron in the artificial neural network is a biomimetic model established by taking the biological nerve cells as the imitation object.…”

Section: Learning Methods Based On Artificialmentioning

confidence: 99%

Data Analysis of Related Factors of Adolescent Physical Exercise Behavior Based upon Artificial Neural Network Model

Chen

Dai

Ren

2022

Wireless Communications and Mobile Computing

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“…As shown in Figure 4 , it can be seen that the RNN hierarchical structure ratio is mainly composed of the input layer, the hidden layer, and the output layer. The arrow in the “hidden layer” indicates that the data is being updated regularly [ 16 ].…”

Section: Neural Network Model Based On Volleyball Arm Recognitionmentioning

confidence: 99%

Recognition of Volleyball Player’s Arm Motion Trajectory and Muscle Injury Mechanism Analysis Based upon Neural Network Model

Zhao

2022

Journal of Healthcare Engineering

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At present, in sports training for volleyball, it still mainly depends on the personal experience of the coach. Training costs are high, and the quality is difficult to maintain stable. Even with the introduction of training assistance software, it is often necessary to manually enter complex data, and the research samples are mostly single individuals. Serving is one of the basic and important technical movements of volleyball, and its standardization is of great significance to the stable performance of the scene. This article proposes an analysis of the volleyball player’s arm trajectory based on the background of human posture recognition and analysis, based on the neural network model. The changes in the angles of the shoulders, elbows, and wrist when serving the ball reflect the different trajectories of the arm. Experiments show that the height of the throwing arm from the ground accounts for 98% of the height. The horizontal angle of the throwing arm at the moment the ball leaves the hand is positively correlated with the throwing time and height, and the reasonable trajectory has an impact on the stability of the throwing ball. The closer the trajectory of the tossing arm is to the vertical, the more stable the tossing is.

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“…In order to design, optimize and control complex HVAC systems, several ML based models have been presented in the past. Park et al (2018) presented an hourly GSHP system performance prediction model based on a multiple linear regression (MLR) and an artificial neural network (ANN). Entering source-side temperature, both entering and leaving load-side temperatures, ambient air temperature along with the heating load data was used to predict the system overall Coefficient of Performance (COP).…”

Section: Literature Reviewmentioning

confidence: 99%

Proceedings of the IGSHPA Research Track 2022

2022

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This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doepublic-access-plan).

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Application of a multiple linear regression and an artificial neural network model for the heating performance analysis and hourly prediction of a large-scale ground source heat pump system

Cited by 79 publications

References 21 publications

Data Analysis of Related Factors of Adolescent Physical Exercise Behavior Based upon Artificial Neural Network Model

Data Analysis of Related Factors of Adolescent Physical Exercise Behavior Based upon Artificial Neural Network Model

Recognition of Volleyball Player’s Arm Motion Trajectory and Muscle Injury Mechanism Analysis Based upon Neural Network Model

Proceedings of the IGSHPA Research Track 2022

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