cost index
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Abstract With the reform of China’s power system, power transmission and transformation project (hereinafter referred to as PTATP) are gradually developing in the direction of integration, informatization, large-scale and systematization. Therefore, the traditional project cost can no longer meet the needs of the society, which requires the project cost based on BD (hereinafter referred to as BD) technology. Through the information platform (hereinafter referred to as IPF), we can collect a lot of information, including policies and regulations database, talent and machine price information database, project cost index database, industry information database, etc., which will provide important support for project cost. Project cost informatization will solve the problems of low information sharing rate, low information value and high information cost, which will more scientifically complete the cost of PTATP. Based on BD technology, we can collect, sort out and analyze the cost information data of PTATP, which will fully explore the data value. Firstly, this paper analyzes the main algorithms needed for project cost. Finally, this paper constructs a PTATP cost IPF based on BD analysis, which will provide accurate countermeasures.

Natural disasters whose scale of damage exceeds the level that regional governments can afford are increasing. As such disasters have increased, the damage to local communities tends to be prolonged. Accordingly, it is important to prevent prolonged disaster damage and secure resilience to ensure quick recovery from the damage. This study analyzed the regional factors that can affect resilience to disaster, quantifying the regional resilience of each sigungu administrative district in Korea that suffered damage from natural disasters during the period 2010-2017 using the resilience cost index (RCI). We investigated the relationship between change in resilience cost index by year and changes in regional factors by year to identify the regions where industrial diversity was secured so as to reduce the exposure of each industry to disaster, budgets for social welfare were increased, and participation in volunteer activities was expanded, all of which tend to improve regional resilience.

Hydraulic excavators are one type of construction equipment used in various construction sites worldwide, and their usage and scale are diverse. Generally, the work efficiency of a hydraulic excavator largely depends on human operation skills. If we can comprehend the experienced operation skills and utilize them for manual control assist, semi-automatic or automatic remote control, it would improve its work efficiency and suppress personnel costs, reduce the operator’s workload, and improve his/her safety. In this study, we propose a methodology to design efficient machine trajectories based on mathematical models and numerical optimization, focusing on ground-level excavation as a dominant task. First, we express its excavation trajectory using four parameters and assume the models for the amount of excavated soil and the reaction force based on our previous experiments. Next, we combine these models with a geometrical model for the hydraulic excavating machine. We then assign the amount of soil to a performance index preferably to be maximized and the amount of work to a cost index preferably to be minimized, both in the form of functions of the trajectory parameters, resulting in an optimization problem that trades them off. In particular, we formulate (1) a multi-objective optimization problem maximizing a weighted linear combination of the amount of soil and the amount of work as an objective function, and (2) a single-objective optimization problem maximizing the amount of soil under a given upper bound on the amount of work, so that we can solve these optimization problems using the genetic algorithm (GA). Finally, we conclude this paper by suggesting our notice on design methodology and discussing how we should provide the optimization method as mentioned above to the users who operate hydraulic excavators.

Abstract It is of great reference significance for broadening the research perspective of environmental issues, improving the efficiency of government environmental governance and the credibility of the government, to scientifically measure and analyze the political cost of environmental issues. This article takes the typical case “protest event of power generation project of R steel plant in T city, China” as the research background. First, the generation process and action mechanism of the political cost of environmental issues in the actual situation are investigated. Then, through in-depth interview, multi-case grounded theory and fuzzy subordinate function analysis, the scientific construction of the political cost index system of environmental issues are completed. Finally, based on G1 method/entropy method combined with weighting and fuzzy comprehensive evaluation method, the political cost of the protest events of R iron and steel plant in T city is measured. The results show that (1) it is important that good single dimensions and reliable indicators are embodied in the overall political cost scale. Among them, the behavioral political cost of the masses is the largest proportion of all indicators; (2) after the entire environmental mass incident is over, the political costs are difficult to repair, and some lagging ideas and behaviors shown by local governments lead to a continuous expansion of the political cost associated with environmental issues; and (3) local governments should not conceal information asymmetry. Instead, local governments should give greater freedom to other actors to deal with environmental problems. This will mitigate the effect of political costs. Corresponding policy recommendations are proposed.

Aviation contribution to global warming and anthropogenic climate change is increasing every year. To reverse this trend, it is crucial to identify greener alternatives to current aviation technologies and paradigms. Research in aircraft operations can provide a swift response to new environmental requirements, being easier to exploit on current fleets. This paper presents the development of a multi-objective and multi-phase 4D trajectory optimization tool to be integrated within a Flight Management System of a commercial aircraft capable of performing 4D trajectory tracking in a Free Route Airspace context. The optimization algorithm is based on a Chebyshev pseudospectral method, adapted to perform a multi-objective optimization with the two objectives being the Direct Operating Cost and the climate cost of a climb-cruise-descent trajectory. The climate cost function applies the Global Warming Potential metric to derive a comprehensive cost index that includes the climate forcing produced by CO2 and non-CO2 emissions, and by the formation of aircraft-induced clouds. The output of the optimization tool is a set of Pareto-optimal 4D trajectories among which the aircraft operator can choose the best solution that satisfies both its economic and environmental goals.

Treadmill walking is commonly used for fitness testing and training. Purpose of present study was to determine whether holding the front hand rails makes any significant change in energy expenditure during treadmill walking or not. Thirty volunteers (17 male and 13 female) participated in the study. Subjects were asked to walk on treadmill at speed of 1.0 to 6.0 mph with and without holding the front hand rails for 6 minutes. Physiological cost index was measured for two different positions and compared for statistically significant difference. Results showed that there was no significant difference (p > 0.05) in Physiological cost index measured for two different positions. Hence, present study concludes that, holding the front hand rails does not make any significant difference in energy expenditure while walking on treadmill. Keywords: Treadmill walking, Physiological cost index, Hand rail.

In this paper, an optimal sizing and placement framework (OSPF) is performed for electric parking lots integrated with wind turbines in a 33-bus distribution network. The total objective function is defined as minimizing the total cost including the cost of grid power, cost of power losses, cost of charge and discharge of parking lots, cost of wind turbines as well as voltage deviations reduction. In the OSPF, optimization variables are selected as electric parking size and wind turbines, which have been determined optimally using an intelligent method named arithmetic optimization algorithm (AOA) inspired by arithmetic operators in mathematics. The load following strategy (LFS) is used for energy management in the OSPF. The OSPF is evaluated in three cases of the objective function such as minimizing the cost of power losses, minimizing the network voltage deviations, and minimizing the total objective function using the AOA. The capability of the AOA is compared with the well-known particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms for solving the OSPF in the last case. The findings show that the power loss, voltage deviations, and power purchased from the grid are reduced considerably based on the OSPF using the AOA. The results show the lowest total cost of energy and also minimum network voltage deviation (third case) by the AOA in comparison with the PSO and ABC with a higher convergence rate, which confirms the better capability of the proposed method. The results of the first and second cases show the high cost of power purchased from the main grid as well as the high total cost. Therefore, the comparison of different cases confirms that considering the cost index along with losses and voltage deviations causes a compromise between different objectives, and thus the cost of purchasing power from the main network is significantly reduced. Moreover, the voltage profile of the network improves, and also the minimum voltage of the network is also enhanced using the OSPF via the AOA.

Value engineering is a method of selecting the optimum design by evaluating the value of the original design and the alternative design. However, if the function score and the cost score of the evaluation subject are indexed, the range of the function index, the cost index and the value index calculated according to the functional attribute and the cost attribute may vary. The client is confused in the decision-making process of selecting the optimum design because the calculation range of the function, cost and value scores are different according to the evaluation subject. The necessity of indexing the cost score and the function score has been constantly raised, but it has been regarded as a difficult problem. This study presents a model that can index the function, cost and value scores using vector normalization method. Additionally, by applying this study model to the case of selecting finishing materials for the office automation floor of a building, the consistency of the study model was verified.