scholarly journals Research on Influencing Factor Selection of Pilot’s Intention

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Haibo Wang ◽  
Ting Pan ◽  
Haiqing Si ◽  
Yao Li ◽  
Naiqi Jiang
Keyword(s):  
Influencing Factors ◽  
Flight Control ◽  
Influencing Factor ◽  
Physical Parameters ◽  
Cognitive State ◽  
Factors Affecting ◽  
Active Safety System ◽  
Factor Sequence ◽  
Automatic Pilot ◽  
Selection Of

The physiological, psychological, and physical characteristics of the pilot will have an impact on flight safety, mainly in the pilot’s intention. In another word, this means the pilot’s psychological experience of flight status under the influence of various factors and the preference for decision-making or behavioral value that is displayed. The pilot’s intention is to reflect the cognitive state that the pilot showed during the maneuvering of the aircraft. The exploration of intention is very important for the study of automatic pilot and flight control active safety system. Also, it is an important concept often involved in the study of human factors in flight, especially the microbehavior of pilots. Pilot’s intention is taken as the study object in this paper; physiological-psychological-physical parameters are obtained through analyzing their influencing factors from the simulating flight experiments designed. The random forest analysis method is used to rank the main influencing factors affecting the pilot’s intention, and the factor sequence is formed. The results provide a good foundation for further research on the pilot’s intention identification.

scholarly journals Choice Model and Influencing Factor Analysis of Travel Mode for Migrant Workers: Case Study in Xi’an, China

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Hong Chen ◽  
Zuo-xian Gan ◽  
Yu-ting He
Keyword(s):  
Influencing Factors ◽  
Migrant Workers ◽  
Choice Model ◽  
Mode Choice ◽  
Influencing Factor ◽  
Travel Mode ◽  
Factors Affecting ◽  
Travel Choice ◽  
Travel Mode Choice ◽  
Set Up

Based on the basic theory and methods of disaggregate choice model, the influencing factors in travel mode choice for migrant workers are analyzed, according to 1366 data samples of Xi’an migrant workers. Walking, bus, subway, and taxi are taken as the alternative parts of travel modes for migrant workers, and a multinomial logit (MNL) model of travel mode for migrant workers is set up. The validity of the model is verified by the hit rate, and the hit rates of four travel modes are all greater than 80%. Finally, the influence of different factors affecting the choice of travel mode is analyzed in detail, and the inelasticity of each factor is analyzed with the elasticity theory. Influencing factors such as age, education level, and monthly gross income have significant impact on travel choice mode for migrant workers. The elasticity values of education degree are greater than 1, indicating that it on the travel mode choice is of elasticity, while the elasticity values of gender, industry distribution, and travel purpose are less than 1, indicating that these factors on travel mode choice are of inelasticity.

scholarly journals Analysis of Influencing Factors of Heat Load of Heating Power Station

2021 ◽  
Vol 252 ◽  
pp. 01042
Author(s):  
Yu Lu ◽  
Rui Li
Keyword(s):  
Influencing Factors ◽  
Heat Load ◽  
Load Forecasting ◽  
Heating System ◽  
Heating Power ◽  
Power Station ◽  
System Planning ◽  
Factors Affecting ◽  
Heating Load ◽  
Selection Of

Heating system load forecasting is very important in heating system planning and formulating heating plans. More accurate load forecasting can obtain greater economic and social benefits for the heating power station. The selection of influencing factors affecting heating load forecasting has a decisive effect on the accuracy of load forecasting. Based on the analysis of heat load of typical heating power station, this paper compares and analyses the influence of outdoor temperature, wind speed and load of previous days, etc. The main factors that should be considered in heating load forecasting are obtained.

scholarly journals Factors Affecting the Promotion of Conservation Tillage in Black Soil—The Case of Northeast China

2021 ◽  
Vol 13 (17) ◽  
pp. 9563
Author(s):  
Yan Qu ◽  
Chulin Pan ◽  
Hongpeng Guo
Keyword(s):  
Influencing Factors ◽  
Soil Conservation ◽  
Northeast China ◽  
Conservation Tillage ◽  
New Technology ◽  
Influencing Factor ◽  
Economic Factor ◽  
Black Soil ◽  
Agricultural Machinery ◽  
Factors Affecting

Taking the conservation tillage influences of black soil in Northeast China as the research object, the paper is written according to the advice of relevant experts and technicians in Northeast China, the study also calculates the weight of each influencing factor through the Delphi and Analytic Hierarchy Process (AHP) method. Then, the significance of the factors affecting the benefit of conservation tillage is analyzed. The results show that, based on the comprehensive analysis, it is concluded that the economic factor is the primary factor affecting the benefit of black soil conservation tillage in Northeast China. Among the twelve influencing factors, eight of them have a significant impact on the development of conservation tillage benefits on black soil in Northeast China. Such as the degree of government subsidy; the adaptability of agricultural machinery; the input of new technology; relevant policies, laws and regulations; the quality of conservation tillage; the income of agricultural machinery farmers; practical application capacity; government publicity. Therefore, in the process of implementing the black soil conservation tillage, we should focus on these influencing factors, which will effectively promote the sustainable development of agriculture in Northeast China.

Methode zur Bestimmung der notwendigen Automatisierung von LKT-Systemen/Determining the necessary automation of storage, commissioning and transport systems

2020 ◽  
Vol 110 (03) ◽  
pp. 141-145
Author(s):  
Maren Müller ◽  
Anke Maria Behrend ◽  
Malte Stonis
Keyword(s):  
Influencing Factors ◽  
Influencing Factor ◽  
Transport Systems ◽  
Selection Of

Die Auswahl von Lager-, Kommissionier- und Transportsystemen (LKT-Systeme) ist aufgrund der hohen Anzahl an zur Verfügung stehenden Systemen am Markt und zu betrachtenden Einflussfaktoren sehr komplex. Ein wichtiger Einflussfaktor ist die Automatisierung. Zur Einordnung der Automatisierungsgrade von LKT-Systemen und zur Bestimmung der individuell notwendigen Automatisierung wird folgend eine Methode vorgeschlagen.   The selection of storage, commissioning and transport systems (sct systems) is very complex due to the large number of available systems on the market and influencing factors. One important influencing factor is automation. To classify the degrees of automation of sct systems and to determine the individually required automation a method is proposed below.

scholarly journals Influencing Factors and Strategies of the Flow of Academic Professionals in Colleges and Universities Based on Convolutional Neural Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
LIli Zhao
Keyword(s):  
Influencing Factors ◽  
Research Universities ◽  
Factor Model ◽  
Influencing Factor ◽  
Colleges And Universities ◽  
Factors Affecting ◽  
Strength Factor ◽  
Mobility Factor ◽  
Questionnaire Surveys ◽  
Academic Professionals

The influencing factors of academic professional mobility in colleges and universities are complex and diverse, and the intensity of each influencing factor has obvious characteristics of differentiation. However, scholars have few relevant studies based on the intensity of factors affecting the flow of academic professionals in colleges and universities. Therefore, this article aims to study and analyze the influence of different factors on the flow of academic professionals in different types of colleges and universities, which is of great significance for promoting the rational and orderly flow of academic professionals. This paper proposes a comprehensive application of multiple methods, such as questionnaire surveys and data statistics, based on ERG theory, based on the four types of universities and colleges: research-oriented, teaching research, teaching, and application. The influence intensity of the flow-influencing factors is comparatively studied. It clarified the differences in the influence of spiritual factors, economic factors, and social factors on the mobility of academic professionals in colleges and universities, established a mobility factor model, and put forward policy recommendations for colleges and universities to promote the rational and orderly mobility of academic professionals. A total of 2042 questionnaires on “Policy Improvement Factors Affecting the Flow of Academic Experts in Universities” were released, four academic experts of different levels were assigned to universities, and 1,561 were effectively searched. Among them, there were 336 research universities, 157 educational research universities, 404 educational universities, and 164 applied universities. The experimental results of this article show that the factors affecting the flow of academic professionals in universities include economic strength factor of 0.4945, social strength factor of 0.5456, and intellectual strength factor of 0.52. Therefore, the factors affecting the mobility of university scholars can be used in strategic research.

scholarly journals Experimental Study on Factors Affecting Interlayer Shear Strength of Fiber Seal

2012 ◽  
Vol 5 ◽  
pp. 253-258
Author(s):  
Peng Cao ◽  
De Cheng Feng ◽  
Chun Wei Gong ◽  
Yin Zhao
Keyword(s):  
Shear Strength ◽  
Orthogonal Experiment ◽  
Influencing Factor ◽  
Fiber Content ◽  
Range Analysis ◽  
Factors Affecting ◽  
Interlayer Shear ◽  
And Performance ◽  
Interlayer Shear Strength ◽  
Selection Of

In order to study influence of different factors on interlayer shear strength of fiber seal, an orthogonal experiment about four factors, respectively, test temperature, fiber content, asphalt content and gravel coverage, and three levels are developed with bevel shear test. The influence rules are evaluated by range analysis method. The result demonstrated that fiber content is the most correlative influencing factor. Thus provides a basis for the selection of material and performance of the fiber seal.

Selection of factors affecting increase of non-oil export

2018 ◽  
Vol 13 (1) ◽  
pp. 45-52
Author(s):  
Aynura Manaf kizi Ismayilova ◽  
Keyword(s):  
Factors Affecting ◽  
Oil Export ◽  
Selection Of

Regional, institutional and individual factors affecting selection of minimally invasive nephroureterectomy in Japan: A national database analysis

2012 ◽  
Vol 20 (7) ◽  
pp. 695-700 ◽  
Author(s):  
Toru Sugihara ◽  
Hideo Yasunaga ◽  
Hiromasa Horiguchi ◽  
Tetsuya Fujimura ◽  
Hiroaki Nishimatsu ◽  
...  
Keyword(s):  
Minimally Invasive ◽  
National Database ◽  
Individual Factors ◽  
Database Analysis ◽  
Factors Affecting ◽  
Selection Of

scholarly journals Aphid–Plant–Phytovirus Pathosystems: Influencing Factors from Vector Behaviour to Virus Spread

Agriculture ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 502
Author(s):  
Junior Corneille Fingu-Mabola ◽  
Frédéric Francis
Keyword(s):  
Influencing Factors ◽  
Virus Transmission ◽  
Physical Factors ◽  
Factors Affecting ◽  
Vector Borne Diseases ◽  
Vector Behaviour ◽  
Crop Fields ◽  
Host Seeking ◽  
The Impact ◽  
Vector Efficiency

Aphids are responsible for the spread of more than half of the known phytovirus species. Virus transmission within the plant–aphid–phytovirus pathosystem depends on vector mobility which allows the aphid to reach its host plant and on vector efficiency in terms of ability to transmit phytoviruses. However, several other factors can influence the phytoviruses transmission process and have significant epidemiological consequences. In this review, we aimed to analyse the aphid behaviours and influencing factors affecting phytovirus spread. We discussed the impact of vector host-seeking and dispersal behaviours mostly involved in aphid-born phytovirus spread but also the effect of feeding behaviours and life history traits involved in plant–aphid–phytovirus relationships on vector performances. We also noted that these behaviours are influenced by factors inherent to the interactions between pathosystem components (mode of transmission of phytoviruses, vector efficiency, plant resistance, …) and several biological, biochemical, chemical or physical factors related to the environment of these pathosystem components, most of them being manipulated as means to control vector-borne diseases in the crop fields.

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