4.1 BIM evaluation and Application
In the design stage, public buildings must meet the requirements of all control elements in the standard, and are divided into three green levels according to the satisfaction of general projects and expected projects.
Whether it is an ordinary project or a preferred project, there are assessment points in the assessment process, and relevant supporting materials must be submitted. For example, the terms of saving land and external environment "do not bring light pollution to surrounding buildings and do not affect the sunshine required by surrounding residential buildings". In the evaluation, the first thing to consider is whether to use high reflection mirror aluminum alloy decorative exterior wall or glass curtain wall; Whether the outdoor landscape light is directly into the air, etc. The supporting materials to be submitted include drawings, design descriptions and inspection reports of the day provided by the design unit. In addition, there are also relevant requirements for certification materials, such as the spatial relationship between surrounding residential buildings and new projects through the general plan; When it is necessary to adopt glass curtain wall design, the light pollution caused by the curtain wall to surrounding buildings shall be provided in relevant design documents and analysis reports. It can be said that the evaluation points and requirements of the test materials explain the provisions of the green building evaluation standards.
4.2 Design method
During the BIM -based green architectural design process, professionals from various tasks such as designers, engineers and other types of work participated in each design process, and coordinated people to provide a basis for decision -making. In different design stages, the role and importance of design participants are constantly adjusted. Figure 1 lists the development of the main participants in the design of the BIM -based green building design.
The concept design almost depends on the knowledge and experience of architects in conventional design. After the plan is formed, it is passed on to other members of the design team for refinement and analysis. If the analysis results do not meet the construction goals, the plan should be modified according to the feedback to form an alternative plan before analyzing. After the project is finalized, it takes a lot of time to deepen the design and drawing construction drawings. This can be clearly seen from Fig. 2.
4.3 Design evaluation and influencing factors
An effective evaluation must first establish an evaluation index system, which is a unified scale to compare and measure various factors. The goal itself is a description of the general effect that can be achieved in any system. Generally speaking, this description is abstracted and blurred, and does not include conditions and measurable values that are directly used as the basis of assessment. The construction of the evaluation index system, as the requirements for the reasonable implementation of the entire evaluation, must follow three basic principles, namely:
Target -oriented: First explain the evaluation requirements and target orientation, the goal as the center of the evaluation indicator system, and guide the evaluation indicators to be closer to the direction of real and comprehensive behavior. The guidance principle requires the value evaluation direction of each indicator in the system to be equal and consistent with the goals.
Reasonable structure: After the overall goal is clear, the next step is to form a reasonable indicator hierarchical structure. The indicators of each layer of the system should be unique, complete and relatively independent, to avoid each other or overlap.
The indicators are the same: The final evaluation is the comparison of the indicator and the system factors. The evaluation indicators should adopt unified or recognized concepts and standards as much as possible, eliminate or correct uncertain factors and inconsistent factors, so that the evaluation indicators will always penetrate the system, similar to the evaluation model.
It is mainly composed of design quality problems and related influencing factors, as shown in Fig. 3.
This article proposes a comprehensive meteorological indicator, that is, human comfort indicators, and its expression method is shown in 8:
$$\text{D}=\text{f}\left(\text{T}\right)+\text{g}\left(\text{U}\right)+\text{h}\left(\text{V}\right)$$
6
In the formula, D is the comfort index of the human body; T is the average daily temperature, and the unit's degree Celsius; U is a daily average relative humidity, the unit is%; V is the average daily wind speed, and the unit is M/S. It is recommended to use the temperature index to predict the comfort of the human body and the relationship between the temperature index and the indoor temperature. It can be expressed as a formula 9:
$${\text{E}}_{\text{t}}={\text{T}}_{\text{d}}-0.55\times (1-\text{R})\left({\text{T}}_{\text{d}}-58\right)$$
7
When using the support vector machine algorithm to predict the modeling, the basic idea is: the input space X in the input space is mapped to the high -vitamin symbol space through non -linear mapping ϕ (x), and then the high -dimensional linear space is returned.
$$\text{y}=\text{f}\left(\text{x}\right)={\text{w}}^{\text{T}}{\phi }\left(\text{x}\right)+\text{b},\text{b}\in \text{R}$$
8
The maximum value of the ai solution function:
$$\text{Q}\left(\text{a}\right)=\sum _{\text{i}=1}^{\text{n}} {\text{a}}_{\text{i}}-\frac{1}{2}\sum _{\text{i},\text{j}=1}^{\text{n}} {\text{a}}_{\text{i}}{\text{a}}_{\text{j}}{\text{y}}_{\text{i}}{\text{y}}_{\text{j}}\left({\text{x}}_{\text{i}}\cdot {\text{x}}_{\text{j}}\right)$$
9
Here is a nuclear function K to achieve non -linear transformation. The nuclear function meets K (xi, XJ) = ϕ (xi) ϕ (yj).
$$\text{Q}\left(\text{a}\right)=\sum _{\text{i}=1}^{\text{n}} {\text{a}}_{\text{i}}-\frac{1}{2}\sum _{\text{i},\text{j}=1}^{\text{n}} {\text{a}}_{\text{i}}{\text{a}}_{\text{j}}{\text{y}}_{\text{i}}{\text{y}}_{\text{j}}\times \text{K}\left({\text{x}}_{\text{i}}\cdot {\text{x}}_{\text{j}}\right)$$
10
From the literature knowledge, it can be seen that if the prior knowledge of the model is lacking, the SVM algorithm based on the radial base function (RBF) is better than other nuclear functions. The mathematical formula is:
$$\text{K}\left({\text{x}}_{\text{i}},{\text{x}}_{\text{j}}\right)=\text{e}\text{x}\text{p}\left[-\frac{{\left({\text{x}}_{\text{i}}-{\text{x}}_{\text{j}}\right)}^{2}}{{{\sigma }}^{2}}\right]$$
11
From the data set collected by the experiment, 200 data groups are selected as a sample set in the sequential order, and the other 25 data groups are used as prediction sets. The prediction results of different models are compared to Fig. 4.
According to the experimental data in Table 3, the model prediction results will be affected by many factors, including training methods and modeling methods.
Table 3
Comparison of indoor environmental parameter modeling results
Modeling method | Number of iterations | Average error rate |
APSO-SVM | 58 | 6.45% |
APSO-FKNN | 113 | 8.51% |
AGA-SVM | 99 | 10.67% |
AGA-FKNN | 152 | 13.58% |