Forecast Model of Phreatic Surface on Tailings Dam Based on GM-GRNN Theory

2010 ◽  
Vol 44-47 ◽  
pp. 3403-3407
Author(s):  
Fei Yue Wang ◽  
Zhi Sheng Xu ◽  
Long Jun Dong
Keyword(s):  
Prediction Method ◽  
Forecast Model ◽  
Random Disturbance ◽  
Tailings Dam ◽  
Phreatic Surface ◽  
Factors Affecting ◽  
Depth Analysis ◽  
Tailing Dam ◽  
Calculation Results ◽  
Surface Prediction

Due to the extremely complicated seepage boundary conditions of tailing dam, the calculation results adopting two-dimensional simplified theory may greatly different from the measured results. It is urgent need of an accurate calculation method to forecast phreatic surface. In-depth analysis of factors affecting tailings dam phreatic surface, phreatic surface prediction model based on GRNN and GM (1,1) was established. A tailing dam engineering is tested using this model. It shows that the model uses the advantages of "accumulative generation" of a Gray prediction method, which weakens the original sequence of random disturbance factors, and increases the regularity of data. It also makes full advantage of the GRNN approximation performance, which has a fast solving speed, describes the nonlinear relationship easily, and avoids the defects of Gray theory.

Phreatic Line Predicted Method-Based SVM for Stability Analysis of Tailing Dam

2010 ◽  
Vol 44-47 ◽  
pp. 3398-3402 ◽  
Author(s):  
Fei Yue Wang ◽  
Long Jun Dong ◽  
Zhi Sheng Xu
Keyword(s):  
Stability Analysis ◽  
Tailings Dam ◽  
Analysis Method ◽  
Affecting Factors ◽  
Accurate Calculation ◽  
Phreatic Surface ◽  
Daily Observation ◽  
Tailing Dam ◽  
Calculation Results ◽  
Predicted Model

Phreatic surface is one of the most important factors to influence tailing dam security degree. Due to the extremely complicated seepage boundary conditions of tailing dam, the calculation results adopting two-dimensional simplified theory may be greatly different from the measured results. It is urgent need of an accurate calculation method to forecast phreatic surface. Based on analysis of affecting factors of phreatic surface in tailing dam, the phreatic surface SVM predicted method is bring forward to predict the phreatic surface. According to the daily observation of phreatic surface, the phreatic surface SVM predicted model obtained. Finally, a tailings dam projects is given to illustrate stability analysis method of tailings dam based on Phreatic predicted Method-based SVM.

Study of Fuzzy Random Reliability Model of Tailings Dam under Earthquake Action

2010 ◽  
Vol 44-47 ◽  
pp. 3393-3397
Author(s):  
Fei Yue Wang ◽  
Long Jun Dong ◽  
Zhi Sheng Xu
Keyword(s):  
Zero Point ◽  
Reliability Theory ◽  
Dam Failure ◽  
Tailings Dam ◽  
Tailing Dam ◽  
Calculation Results ◽  
Earthquake Action ◽  
The Stability ◽  
Fuzzy Random

Two kinds of the deficiencies exist in the traditional dam reliability and the safety coefficient calculation methods. First, it is impossible to give accurate mean to design variable in case study, because to large extent, means are greatly influenced by many objective factors or man-made effects, which degree of effects has greater degree of ambiguity. Second, the traditional reliability theory takes zero point as measure of dam’s failure or not, and on both sides of zero point the structure of state mutants from security to failure. But in fact, it’s very hard to give a definite limitation to the dam state from security to failure, because a fuzzy scope exists between stability and failure. On the basis of solving the above two issues, this paper for the first time applies fuzzy reliability theory to the stability research of tailings dam under earthquake action , considering fuzziness of both the event of tailings dam failure and the main variables and parameter. Integrating fuzziness and randomness, this paper explores fuzzy random reliability analysis methods of tailings dam engineering. The results of case study show that the calculation results agree well with the actual situation, this analysis method is more scientific and reasonable than traditional dam safety factor calculation method, and better reflects the real situation. It also provides a new way to calculate stability of tailing dam considering earthquake action.

scholarly journals Core Elements Affecting Sharing: Evidence from the United States

2021 ◽  
Vol 13 (7) ◽  
pp. 3943
Author(s):  
Aurelija Burinskienė ◽  
Edita Leonavičienė ◽  
Virginija Grybaitė ◽  
Olga Lingaitienė ◽  
Juozas Merkevičius
Keyword(s):  
United States ◽  
The United States ◽  
Collaborative Consumption ◽  
Factors Affecting ◽  
Use Of Resources ◽  
Personal Consumption ◽  
Depth Analysis ◽  
Core Elements ◽  
Long Time ◽  
Number Of Visits

The new phenomenon called sharing or collaborative consumption emerged a decade ago and is continuously growing. It creates new possibilities for society, and especially for business, is beneficial for the environment, makes more efficient use of resources, and presents a new competitive business model. The scientific literature lacks a more in-depth analysis of the factors influencing sharing activity growth; therefore, the paper’s authors attempt to fill this gap. The authors aim to identify the factors affecting the use of sharing platforms. To reach the goal, the authors developed a regression model and constructed a list of 71 variables. The study used monthly United States data from January 2017 to June 2020 from the publicly available Federal Reserve Economic Data (FRED)and Google trends databases. The comparison to other indexes proves that the proposed index, representing the number of visits to sharing platforms (SEP), is a unique one. The first index allowed us to revise the sharing activity monthly. The authors identified that variables such as wage level, social network users, import level, and personal consumption are critical in affecting the number of visits to sharing platforms. The presented framework could be helpful for practitioners and policymakers analysing the stimulation of sharing or collaborative consumption. It includes indicators representing different areas, such as society, technology, and country, and allows for monthly investigations. Such activity was evident for a long time when online platforms contributed to its wider accessibility. The results help to forecast the number of visits monthly. Sharing is still an emerging area for research; thus, the authors tried to explore the phenomenon of sharing to expand the conceptual level of knowledge.

Land Subsidence Prediction Method of Power Cables Pipe Jacking Based on the Peck Theory

2013 ◽  
Vol 634-638 ◽  
pp. 3721-3724
Author(s):  
Yuan Liang Zhang ◽  
Yi Hu Zhang
Keyword(s):  
Land Subsidence ◽  
Prediction Method ◽  
Dominant Factor ◽  
Engineering Practice ◽  
Foundation Settlement ◽  
Power Cables ◽  
Overhead Transmission Line ◽  
Allowable Range ◽  
Calculation Results ◽  
Range Calculation

Overhead transmission line and cable are generally used for across or crossing the railway, highways and rivers.For higher deformation requirement of operation of the railway and highway foundation settlement,to ensure that the cable through the process of foundation in regulating the allowable range, calculation and prediction of foundation settlement is specially necessary.Based on the Peck theory, the dominant factor in foundation settlement-strata loss calculation method is introduced supplemented with measured settlement observation records in this paper,which confirmes that the calculation results are replicab in engineering practice.

scholarly journals A study on prediction method for ozone dosage and residual ozone concentration in advanced ozone water treatment

2017 ◽  
Vol 12 (1) ◽  
pp. 87-96 ◽  
Author(s):  
J. S. Hyung ◽  
K. B. Kim ◽  
M. C. Kim ◽  
I. S. Lee ◽  
J. Y. Koo
Keyword(s):  
Water Quality ◽  
Hydrogen Peroxide ◽  
Water Treatment ◽  
Environmental Factors ◽  
Real Time ◽  
Ozone Concentration ◽  
Prediction Method ◽  
Optimum Amount ◽  
Factors Affecting ◽  
Water Treatment Plants

Ozone dosage in most water treatment plants is operated by determining the ozone concentration with the experience of the operation. In this case, it is not economical. This study selected the factors affecting residual ozone concentration and attempted to estimate the optimum amount of hydrogen peroxide dosage for the control of the residual ozone concentration by developing a model for the prediction of the residual ozone concentration. The prediction formulas developed in this study can quickly respond to the environment of water quality and surrounding environmental factors, which change in real time, so it is judged that they could be used for the operation of the optimum ozone process, and the control of ozone dosage could be used as a new method in controlling the concentration of ozone dosage and the concentration of residual ozone.

In-Depth Analysis of Key Factors Affecting the Catalysis of Oxidized Carbon Blacks for Cellulose Hydrolysis

ACS Catalysis ◽  
2021 ◽  
pp. 892-905
Author(s):  
Atsushi Gabe ◽  
Akira Takatsuki ◽  
Masahiko Hiratani ◽  
Masato Kaneeda ◽  
Yoshiaki Kurihara ◽  
...  
Keyword(s):  
Cellulose Hydrolysis ◽  
Key Factors ◽  
Factors Affecting ◽  
Carbon Blacks ◽  
Depth Analysis ◽  
Oxidized Carbon

scholarly journals Subway Tunnel Disease Associations Mining Based on Fault Tree Analysis Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Xiaobing Ding ◽  
Qiuyu Huang ◽  
Haiyan Zhu ◽  
Hua Hu ◽  
Zhigang Liu
Keyword(s):  
Fault Tree ◽  
Fault Tree Analysis ◽  
Monitoring And Control ◽  
Subway Tunnel ◽  
Tree Analysis ◽  
Quantitative Calculation ◽  
Depth Analysis ◽  
Disease Associations ◽  
Calculation Results ◽  
Hot Weather

Monitoring and control of subway tunnel diseases throughout operation determine whether the operation of the subway is safe or not. In order to ensure operation safety, in-depth analysis of tunnel disease risks must be conducted. We constructed a fault tree based on tunnel diseases of Shanghai Subway at first. Using the subway tunnel maintenance work data, we calculated the probability of occurrence of elementary events of the fault tree, conducted quantitative calculation and analysis on the tunnel diseases, and found major diseases of the tunnels and their causes in light of the calculation results. Then, indicated by the precise fault tree analysis (FTA) we conducted, common tunnel diseases mainly include large passenger flow, shortage of maintenance personnel, maintenance error, personal carelessness, hot weather, and poor lighting. Analysis was conducted on the probability importance of elementary events of the tunnel diseases as well. In the end, we proposed the tunnel disease association rule mining algorithm based on the support degree. Via the calculation of association among major diseases, we explored the elaborate association mechanism of the diseases. The in-depth mining on the association mechanism can provide theoretical support and decision support for prevention and comprehensive control of the tunnel diseases and lay a solid foundation of practice guidance for subway operation safety of megacities.

scholarly journals RESULTS OF APPLYING THE METHODOLOGY FOR THE QUANTITATIVE ASSESSMENT CONFIRM THE PREDICTION OF THE 3D MODELFOR HORIZONTAL SECTION OF WELLS

2017 ◽  
pp. 13-19
Author(s):  
R. M. Bembel ◽  
I. A. Schetinin
Keyword(s):  
Quantitative Assessment ◽  
3D Model ◽  
Forecast Model ◽  
Horizontal Section ◽  
Factors Affecting

The article discusses results of the use methodology for quantification of prediction of the 3D model for geosteering. This methodology tested for 90 wells with horizontal completion. According to the obtained statistics to assess factors affecting the reliability of the forecast model and defines the boundary criteria of quality confirmation.

scholarly journals Assessing the caring behaviors of critical care nurses

2018 ◽  
Vol 8 (10) ◽  
pp. 77 ◽  
Author(s):  
Samah Anwar Shalaby ◽  
Nouf Fahad Janbi ◽  
Khairiah Khalid Mohammed ◽  
Kholud Mohammed Al-harthi
Keyword(s):  
Job Satisfaction ◽  
Critical Care ◽  
Educational Background ◽  
Critical Care Nurses ◽  
Affecting Factors ◽  
Caring Behaviors ◽  
Factors Affecting ◽  
Critical Care Units ◽  
Depth Analysis ◽  
The Impact

Objective: To assess the critical care nurses’ perception of their caring behaviors and factors affecting these behaviors.Methods: Participants of this descriptive correlational exploratory study included 277 critical care nurses selected conveniently from nurses worked in all critical care units in King Khalid Hospital, Jeddah. A self-reported questionnaire namely, “Critical Care Nurses Caring Behavior Perception” developed by the researchers after reviewing related literature was used to assess caring behaviors and their affecting factors as perceived by critical care nurses.Results: Seventy percent of the nurses aged between 31 to 50 years old and more than half of nurses had ICU experience ranged from 6 to 10 years, while two thirds of nurses had no previous training about caring behaviors. The study findings revealed that the majority of nurses had high scores of perceived caring behaviors, whereas the mean of their perception was 296.96 ± 18.32. There was a statistical significant positive relationship between nurses’ perception and their work circumstances, workload, job satisfaction, educational background and patient characteristics.Conclusions: It is important to consider critical units’ circumstances, nurses’ educational background, job satisfaction, as well as the nature of critically ill patients in order to promote nurses awareness and implementation of caring behaviors. Moreover, replication of the current study using qualitative approach for in-depth analysis of the impact of factors could affecting caring behaviors on nurses’ perception in various highly specialized critical care units.

Evaluation of innovative development of housing construction in the partition of federal districts

2021 ◽  
pp. 199-223
Author(s):  
Ekaterina Litvinenko
Keyword(s):  
Construction Industry ◽  
Housing Construction ◽  
Purchasing Power ◽  
Innovative Development ◽  
Factors Affecting ◽  
Depth Analysis ◽  
Federal Districts ◽  
The Russian Federation ◽  
Innovative Potential ◽  
North Western

The aim of the study is to assess the innovative potential of housing construction through determining the purchasing power of citizens acquiring housing in the property. In terms of hypothesis the study offers the term of acquiring housing in property as a criterion for this assessment. This indicator displays the change in the purchasing power of citizens under the influence of various externalities. The analysis of this indicator allows us to determine the influence of these factors on the change in the purchasing power of population, to identify the reserves that contribute to its increase, and to identify the policies aimed at innovative development of construction industry. The article assesses the innovative development of housing through an in-depth analysis of factors affecting the change in the term of housing acquisition in the Russian Federation at large, as well as in the context of individual subjects of the Central and North-Western Federal Districts of Russia in the period from 2017 to 2018.

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