Planning Evaluation Model Research Articles

Scenario spatial planning evaluation model for subsidence-economic resilience environment in geohazard prone-coastal megacities: urban underground space (UUS) development in Shanghai by year 2035

Scenario spatial planning evaluation model for subsidence-economic resilience environment in geohazard prone-coastal megacities: urban underground space (UUS) development in Shanghai by year 2035

Retracted: Construction of Landscape Ecological Planning Evaluation Model Based on Sensor Network

Retracted: Construction of Landscape Ecological Planning Evaluation Model Based on Sensor Network

Application of Intelligent Optimization Algorithms in the Distribution Network Planning and Evaluation Models

In order to reasonably plan distribution network evaluation strategies and improve the efficiency and accuracy of power system planning, this study aims to explore the application of intelligent optimization algorithms in distribution network planning and evaluation. It includes the principle, method and model construction of intelligent optimization algorithm, and designs a distribution network planning evaluation model using Ant colony optimization algorithms combined with GIS (Geographic Information System). This article applies its example to the distribution network planning of a certain area, and the results show that compared with traditional algorithms, the intelligent optimization algorithm has a voltage value of 230.2V at the highest and 220.2V at the lowest; The highest load value is 2.75 Megawatt, and the lowest is 1.19 Megawatt; The longest running time is 8913ms, surpassing traditional algorithms in all aspects. This algorithm improves the voltage stability and load balance of the distribution network, and reduces operating time. This study has certain promotion and application value for the research and practical application of power system planning, which can improve the efficiency and accuracy of power system planning and provide scientific basis for the reliability and effectiveness of power supply.

Construction of Landscape Ecological Planning Evaluation Model Based on Sensor Network

The application of wireless sensor network (WSN) technology promotes the modernization of forestry. WSN application technology in forest areas is an important research topic for the sustainable development of forestry in China and is also a research hotspot for forestry ecological monitoring at present. The application of wireless sensor networks in forest areas, first of all, solves the problem of limited energy supply and low-latency data transmission in the forest environment. Due to the large area of the forest environment and uneven tree density, dynamic changes in forest height, easy to block the signal, and other characteristics, the forest environment is prone to node energy depletion fast, the network life cycle is short, and data transmission delays large dilemma. Second, the application of wireless sensor networks is usually centered on maximum data acquisition, but the contradiction between high data acquisition rate and limited energy supply is inevitable, so it is necessary to construct a maximum data acquisition rate model with limited energy supply as a constraint to guarantee the optimal acquisition conditions for wireless sensor networks. In this paper, from the application of wireless sensor network technology in forest environment, the research on the application of wireless sensor network in forestry is carried out around the analysis of energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision-making fire danger warning process, so as to provide a solution to the overall problem of forest fire warning based on rechargeable wireless sensor network. In this paper, we analyze the dynamic replenishment of energy in rechargeable wireless sensor networks and propose an energy-based transmission control protocol that effectively improves data transmission efficiency. In the rechargeable wireless sensor network, the network E2E (end-to-end) average delay time is calculated based on the number of nodes on the data transmission link. The research idea of this paper starts from the application technology of wireless sensor network in the forest environment, and the design of the energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision fire danger warning process are realized vertically.

Rural Planning Evaluation Based on Artificial Neural Network.

The continuation of human civilization is inseparable from the development and construction of rural areas, and infrastructure is the core of rural development. China has been building large-scale rural infrastructure in recent years. Rural infrastructure building, for example, is huge in both quantity and scope, but it is beset by challenges in its current construction and development, and it urgently requires suitable leadership. Planning assessment, as a technical method, can identify problems in regional development and is a powerful tool for evaluating the impact of planning and construction and promoting the development of complete new areas. This paper is aimed at the planning evaluation of rural construction and the evaluation of rural construction and guides the planning and implementation of the next step of rural construction, to assist China's supervision and inspection of rural construction effect and promote rural construction and development into a good track. In view of the low accuracy and efficiency of the current evaluation model of rural planning and the problem that a single neural network easily produces local extreme value, the neural network method is improved, and the application of LM-BP neural network in the evaluation model of rural planning is proposed. Input sample elements are five factors affecting rural construction, including industrial construction, population distribution, and utilization rate of large-scale facilities, construction of public facilities, and promotion effect of supporting policies. Output sample is the evaluation result. On this foundation, the LM-BP neural network was used to convert the training into a least square problem, and the LM method was used to redefine the number of hidden layer nodes, resulting in the construction of a rural planning evaluation model based on the LM-BP neural network. This approach is used to determine the outcomes of rural planning evaluations. The experimental results show that the designed evaluation model has a small evaluation error, has the advantage of high accuracy compared with similar models, and is a reliable evaluation model for rural planning.

Objective evaluation of radiation treatment plans.

The evaluation of radiation treatment plans involves making trade-offs among doses delivered to the tumor volumes and nearby normal tissues. Evaluating state-of-the-art three-dimensional (3D) plans is a difficult task because of the huge amount of planning data that needs to be deciphered. Multiattribute utility theory provides a methodology for specifying trade-offs and selecting the optimal plan from many competing plans. Using multiattribute utility theory, we are developing a clinically meaningful objective plan-evaluation model for 3D radiation treatment plans. Our model incorporates three of the factors involved in radiation treatment evaluation--treatment preferences of the radiation oncologist, clinical condition of the patient, and complexity of the treatment plan.

건설사업 참여주체 별 해외건설공사 국가리스크 핵심요인 도출 및 비교분석

정부는 장기적인 관점에서 해외건설사업의 활성화와 수주 경쟁력 강화에 주력하고 있다. 최근에는 단순 도급공사 뿐만 아니라, 설계 및 엔지니어링, 건설사업관리(CM)) 사업의 해외진출 역시 점진적으로 늘어나는 추세이다. 하지만 현재까지 해당 분야에 대한 리스크 분석 사례는 미미한 실정이다. 이에 본 연구에서는 참여주체 별 해외건설공사 리스크에 대한 비교분석을 위하여 리스크를 계층화하고, 도출 된 리스크요인에 대하여 PI척도를 활용한 전문가 대상 설문을 실시하여 그 특징을 비교하여 보았다. 본 연구의 결과로써, 해외건설 국가리스크를 총 6 Section, 31개의 요소로 계층화 하였고, 이를 기초로하여 참여주체 별 중요도를 도출하였다, 또한 Risk Matrix에 따라 시공사 17개, 설계사 14개, CM사 17개의 핵심리스크 요인을 선정하고 이를 비교 분석 하였다. 본 연구 결과는 향후 건설사업 참여주체 별 사업 특성에 맞는 리스크관리전략 수립 및 평가모델 구축을 위한 기초자료로 활용 가능할 것으로 기대된다. The government has focused on activation of overseas construction projects and strengthening competitiveness in the long term. In recent years Public construction contract as well as design, engineering, construction management(CM) are gradually expanding into other countries, but risk analysis cases in the field are slight. In this study, We utilized PI scale and drew a conclusion about the importance of overseas risk by participants. We compared its features from the risk factor based on Risk Matrix. As a result of this study total of 6 section 31 Country Risk factors for the importance of overseas risk by participants were drawn, and the key risk factors (17 constructor, 14 designers, 17 CMr) based on Risk Matrix were derived. By utilizing the result of this study will be used as the basic data for establishing risk management strategy to meet each business and planning evaluation model.

PET

Energy conservation is a growing important issue in designing modern database management system (DBMS). This requires a deep thinking about the tradeoffs between energy and performance. Despite the significant amount of efforts at the hardware level to make the major components consume less energy, we argue for a revisit of the DBMS query processing mechanism to identify and harvest the potential of energy saving. However, the state-of-art architecture of DBMS does not take energy usage into consideration in its design. A major challenge in developing an energy-aware DBMS is to design and implement a cost-based query optimizer that evaluates query plans by both performance and energy costs. By following such a strategy, our previous work revealed the fact that energy-efficient query plans do not necessarily have the shortest processing time. This demo proposal introduces PET -- an energy-aware query optimization framework that is built as a part of the PostgreSQL kernel. PET, via its power cost estimation module and plan evaluation model, enables the database system to run under a DBA-specified energy/performance tradeoff level. PET contains a power cost estimator that can accurately estimate the power cost of query plans at compile time, and a query evaluation engine that the DBA could configure key PET parameters towards the desired tradeoff. The software to be demonstrated will also include workload engine for producing large quantities of queries and data sets. Our demonstration will show how PET functions via a comprehensive set of views from its graphical user interface named PET Viewer . Through such interfaces, a user can achieve a good understanding of the energy-related query optimization and cost-based plan generation. Users are also allowed to interact with PET to experience the different energy/performance tradeoffs by changing PET and workload parameters at query runtime.

Evaluation of an objective plan-evaluation model in the three dimensional treatment of nonsmall cell lung cancer

Evaluation of three dimensional (3D) radiotherapy plans is difficult because it requires the review of vast amounts of data. Selecting the optimal plan from a set of competing plans involves making trade-offs among the doses delivered to the target volumes and normal tissues. The purpose of this study was to test an objective plan-evaluation model and evaluate its clinical usefulness in 3D treatment planning for nonsmall cell lung cancer. Twenty patients with inoperable nonsmall cell lung cancer treated with definitive radiotherapy were studied using full 3D techniques for treatment design and implementation. For each patient, the evaluator (the treating radiation oncologist) initially ranked three plans using room-view dose-surface displays and dose-volume histograms, and identified the issues that needed to be improved. The three plans were then ranked by the objective plan-evaluation model. A figure of merit (FOM) was computed for each plan by combining the numerical score (utility in decision-theoretic terms) for each clinical issue. The utility was computed from a probability of occurrence of the issue and a physician-specific weight indicating its clinical relevance. The FOM was used to rank the competing plans for a patient, and the utility was used to identify issues that needed to be improved. These were compared with the initial evaluations of the physician and discrepancies were analyzed. The issues identified in the best treatment plan were then used to attempt further manual optimization of this plan. For the 20 patients (60 plans) in the study, the final plan ranking produced by the plan-evaluation model had an initial 73% agreement with the ranking provided by the evaluator. After discrepant cases were reviewed by the physician, the model was usually judged more objective or "correct." In most cases the model was also able to correctly identify the issues that needed improvement in each plan. Subsequent replanning confirmed that further manual plan optimization could be achieved in 17 patients. The objective plan-evaluation model was able to rank lung cancer radiotherapy plans from best to worst. It was useful in improving plans and may be useful to physicians in defining goals for patients based on the ability to effectively and safely treat their tumors.

Validation and clinical usefulness of an objective plan evaluation model in the three-dimensional treatment of non-small cell lung cancer

Validation and clinical usefulness of an objective plan evaluation model in the three-dimensional treatment of non-small cell lung cancer

Experiments with stock control policies and leadtime setting rules, using an aggregate planning evaluation model of a make-for-stock shop

A simulation model, driven by real order time series, of an actual make-for-stock shop is described. A broad spectrum of different sets of decision rules has been incorporated in the model in an attempt to represent as many as possible of the production controls which might be utilized by a production manager. Experiments designed to determine the impact on a production cost function of changes in decision rules can be conducted over a wide range of conditions, with the objective of assessing the robustness of rule changes. To illustrate the use of the model, the results of experiments in two areas of production control are presented. Changing the stock control policy used by the host company to a re-order level policy type was shown to lead to significant improvements in performance across the range of conditions examined, in the case of a low marginal cost of stock review. In experiments with leadtime setting rules, improvements in performance were obtained across the spectrum of experimental conditions when the leadtime distribution was altered to one based on batch work content and number of operations and the tightness of the mean leadtime was simultaneously increased.