scholarly journals Environmental Governance Cost Prediction of Transportation Industry by Considering the Technological Constraints

Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1352
Author(s):  
Suhui Wang ◽  
Fei-Fei Ye
Keyword(s):  
Prediction Model ◽  
Technological Innovation ◽  
Environmental Governance ◽  
Transportation Industry ◽  
Input Output ◽  
Investment Planning ◽  
Cost Prediction ◽  
The Cost ◽  
Technological Constraints ◽  
Governance Costs

In order to solve the problem of environmental governance investment planning in the transportation industry, a cost prediction model is proposed under technological constraints, where the input output indictors emphasizes the flexibility of prediction and its characters are asymmetric, while the constructs of prediction model focuses on the standardization and its characters are symmetrical. The basic principle of the cost prediction model is based on an extended belief rule-based (EBRB) system to model the input-output relationship in investment planning, and a parameter learning model to improve the accuracy of the EBRB system. Additionally, the technological innovation factors are also embedded in the cost prediction model to investigate the influence of technology-related outcomes on investment planning. Finally, based on the data of environmental governance in China’s transportation industry from 2003 to 2016, the cost of transportation industry environmental management in China’s thirty provinces from 2017 to 2033 is predicted under the constraints of technological innovation. Results show that: (1) the accuracy of the proposed cost prediction model is higher than some existing cost prediction methods; (2) the predicted environmental governance costs have a significant regional difference; (3) the upgrading of technological innovation is conducive to saving the future environmental governance costs of the transportation industry in some provinces. In addition to the above results, the present study provides model supports and policy references for government decision makers in transportation industry-related environmental cost planning.

scholarly journals Cost prediction model based on system dynamics in water resource project

2019 ◽  
Vol 258 ◽  
pp. 02027
Author(s):  
Hirijanto ◽  
I Wayan Mundra ◽  
Addy Utomo
Keyword(s):  
Prediction Model ◽  
Cost Estimation ◽  
Construction Projects ◽  
Model Simulation ◽  
Secondary Data ◽  
System Dynamic ◽  
Cost Prediction ◽  
Cost Component ◽  
The Government ◽  
The Cost

Project’s cost is one of important components in project achievement. Because of the uniqueness of construction projects, cost estimation always differs from project to project. The rate of cost components always change over time make difficult to forecast the cost for the upcoming project. The cost component consists of many influencing variables where there is interrelationship each other affecting to the total project cost. This paper objective is to develop a cost prediction model to assist the project planners in cost estimation for future projects. System dynamic is one of the appropriate methods to analyse system behaviour with interrelationship referring to the historic data, so it is able to predict the future project. Developing the model, primary and secondary data are collected from previous studies, interview with the government planner and survey in Malang Regency. The model simulation is Brick work unit with its components. Data from last thirteen years are used to verify and validate the developed model by causal loop diagram as a basic method in system dynamic. The finding showed that the model is closed to real condition through the validation mechanism. The developed system is useful in decision making of budget planning based on work quantity.

scholarly journals Analysis of Environmental Governance Expense Prediction Reform With the Background of Artificial Intelligence

2022 ◽  
Vol 34 (5) ◽  
pp. 1-19
Author(s):  
Xiaohui Wu
Keyword(s):  
Artificial Intelligence ◽  
Environmental Management ◽  
Environmental Governance ◽  
Shared Governance ◽  
Cost Prediction ◽  
Rule Based ◽  
The Public ◽  
General Government ◽  
Equilibrium Approach ◽  
The Cost

In this paper, Artificial Intelligence assisted rule-based confidence metric (AI-CRBM) framework has been introduced for analyzing environmental governance expense prediction reform. A metric method is to assess a level of collective environmental governance representing general, government, and corporate aspects. The equilibrium approach is used to calculate improvements in the source of environmental management based on cost, and it is tailored to test the public sector-corporation for environmental shared governance. The overall concept of cost prediction or estimation of environmental governance is achieved by the rule-based confidence method. The framework compares the expected cost to the environment of governance to determine the efficiency of the cost prediction process.

scholarly journals Cost Control and Project Cost Analysis of Intelligent Building under Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Shengran Xi ◽  
Chunxia Zhang ◽  
Zixi Cai ◽  
Yikang Xu
Keyword(s):  
Internet Of Things ◽  
Prediction Model ◽  
Smart City ◽  
Cost Control ◽  
Smart Cities ◽  
Cost Prediction ◽  
Intelligent Building ◽  
Project Cost ◽  
Total Cost ◽  
The Cost

The conventional urban system has a very disorganized and unmanageable mode of operation, and the information between the systems has not been efficiently shared and interconnected. Smart cities and intelligent building will be the future trend of urban development. With the advent of new concepts and techniques brought by the Internet of Things (IoT) across the world, all fields of life are progressively shifting towards smart societies. Based on the prediction algorithm of the IoT, this paper constructs the cost control and cost prediction model of intelligent building. Combined with the characteristics of the current smart city construction, three engineering cost schemes (S0, S1, and S2) are constructed, and the cost simulation of these three examples is carried out to verify the cost control and cost prediction model of the intelligent building. Experimental results show that the total cost of each cost level of the three schemes is lower than the conventional total cost, and the total cost change rate ranges are −121.6%∼−27.6%, −210.3%∼−47.2%, and −150.3%∼−22.3%, respectively. The proposed smart city cost prediction model can reduce project cost, which has great economic significance for the construction of smart cities.

Economic Aspects of Mustard Cultivation in Lakhimpur Kheri District of Uttar Pradesh

2020 ◽  
pp. 520-523
Keyword(s):  
Average Cost ◽  
Uttar Pradesh ◽  
Net Income ◽  
Economic Aspects ◽  
Positive Relation ◽  
Input Output ◽  
Output Ratio ◽  
Gross Income ◽  
Average Size ◽  
The Cost

The results revealed that on an overall average size of landholding was estimated to be 0.97 ha. The total cultivated area at all categories of sample farms were found to be irrigated. Overall average, cost of cultivation was estimated `27819.43 per ha. The cost of cultivation showed positive relation with size of holding. The cost of cultivation was highest on medium farms (`32549.25) followed by small (`31528.40 and marginal (`29171.74), respectively. Overall average, cost of production was estimated `2446.44 per hectare. On an average input-output ratio on the basis Costs A1/A2, B1, B2, C1, and C2 were recorded 1:2.86, 1:2.77, 1:1.91, 1:1.89 and 1:1.46, respectively. On the basis of Cost C2 input-output ratio was highest on marginal farms (1:1.47) followed by small (1:1.44) and medium (1:1.43), respectively. Overall average, net income and gross income were found `9859.33 and 40028.69 per ha, respectively.

Based on Comparable Price Energy Input-Output Table of Xinjiang to Research Low Carbon Economic Development Strategy

2013 ◽  
Vol 291-294 ◽  
pp. 1573-1576
Author(s):  
Yuan Sheng Huang ◽  
Lu Tong Li
Keyword(s):  
Development Strategy ◽  
Carbon Emissions ◽  
Energy Input ◽  
High Energy ◽  
Low Carbon ◽  
Input Output ◽  
Output Table ◽  
The Mean ◽  
The Cost ◽  
Advanced Production

Based on the input-output theory, the paper using the comparable price energy input-output table,quantitatively estimates the implicit carbon emissions of each industrial department,and analyzes the growth of the implicit carbon emissions of the resident consumption through the structure decomposition.Conclusion indicates:From 1992 to 1997, the mean of the implicit carbon emissions of each industrial department in Xinjiang had been rising; From 1997 to 2007, the mean of the implicit carbon emissions of each industrial department had been declining;The implicit carbon emissions of Hydropower industry, the fire power and other seven similar industrial department were higher than that of each industrial department so that Xinjiang should strengthen monitoring on the high energy consumption.The implicit carbon emissions of the resident consumption was still in the trend of ceaseless growth and all of that states clearly that the economic grows at the cost of the increase of the greenhouse gas emissions.Xinjiang should introduce foreign advanced production technology,further optimizing the structure of the resident consumption.

A Novel Effort Measure Method for Effort-Aware Just-in-Time Software Defect Prediction

2021 ◽  
Vol 31 (08) ◽  
pp. 1145-1169
Author(s):  
Liqiong Chen ◽  
Shilong Song ◽  
Can Wang
Keyword(s):  
Prediction Model ◽  
Defect Prediction ◽  
Software Systems ◽  
Support Vector ◽  
Just In Time ◽  
Software Defect Prediction ◽  
Fine Grained ◽  
Software Defect ◽  
Code Changes ◽  
The Cost

Just-in-time software defect prediction (JIT-SDP) is a fine-grained software defect prediction technology, which aims to identify the defective code changes in software systems. Effort-aware software defect prediction is a software defect prediction technology that takes into consideration the cost of code inspection, which can find more defective code changes in limited test resources. The traditional effort-aware defect prediction model mainly measures the effort based on the number of lines of code (LOC) and rarely considers additional factors. This paper proposes a novel effort measure method called Multi-Metric Joint Calculation (MMJC). When measuring the effort, MMJC takes into account not only LOC, but also the distribution of modified code across different files (Entropy), the number of developers that changed the files (NDEV) and the developer experience (EXP). In the simulation experiment, MMJC is combined with Linear Regression, Decision Tree, Random Forest, LightGBM, Support Vector Machine and Neural Network, respectively, to build the software defect prediction model. Several comparative experiments are conducted between the models based on MMJC and baseline models. The results show that indicators ACC and [Formula: see text] of the models based on MMJC are improved by 35.3% and 15.9% on average in the three verification scenarios, respectively, compared with the baseline models.

scholarly journals Who Should Regulate Disruptive Technology?

2019 ◽  
Vol 10 (1) ◽  
pp. 4-22 ◽  
Author(s):  
Marta Katarzyna KOŁACZ ◽  
Alberto QUINTAVALLA ◽  
Orlin YALNAZOV
Keyword(s):  
Technological Innovation ◽  
New Technologies ◽  
The Other ◽  
Disruptive Technology ◽  
Primary Concern ◽  
Cost And Benefit ◽  
Innovation Cost ◽  
The Cost ◽  
Risky Technology ◽  
Law Making

The primary concern of the present paper is the cost of acquiring information by judges and legislators in the process of regulating new technologies. The paper distinguishes between risky and uncertain applications of technology. A risky technology poses an obvious risk, and the problem before the regulator is one of comparing cost and benefit. We argue that the judiciary, which acquires information gratis from litigants, is better suited to the regulation of risky technologies. Uncertain technologies, on the other hand, can be harmful in ways which cannot be foreseen at the time of the technological innovation. Cost and benefit are incalculable; regulation must instead be based on subjective preferences about the degree of uncertainty that society should tolerate. Legislative law-making is designed with a view to aggregating subjective preferences. Accordingly, uncertain technologies should be regulated through statute.

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