Qualitative Evaluation Index Research Articles

3D medical image segmentation using the serial–parallel convolutional neural network and transformer based on cross‐window self‐attention

AbstractConvolutional neural network (CNN) with the encoder–decoder structure is popular in medical image segmentation due to its excellent local feature extraction ability but it faces limitations in capturing the global feature. The transformer can extract the global information well but adapting it to small medical datasets is challenging and its computational complexity can be heavy. In this work, a serial and parallel network is proposed for the accurate 3D medical image segmentation by combining CNN and transformer and promoting feature interactions across various semantic levels. The core components of the proposed method include the cross window self‐attention based transformer (CWST) and multi‐scale local enhanced (MLE) modules. The CWST module enhances the global context understanding by partitioning 3D images into non‐overlapping windows and calculating sparse global attention between windows. The MLE module selectively fuses features by computing the voxel attention between different branch features, and uses convolution to strengthen the dense local information. The experiments on the prostate, atrium, and pancreas MR/CT image datasets consistently demonstrate the advantage of the proposed method over six popular segmentation models in both qualitative evaluation and quantitative indexes such as dice similarity coefficient, Intersection over Union, 95% Hausdorff distance and average symmetric surface distance.

Research on Evaluation System of Medical Imaging Equipment Dynamic Acquisition Technology Based on Multiple Criteria Decision Analysis

To construct an evaluation model system for dynamic data acquisition methods of medical imaging equipment in hospitals. The analytic hierarchy process (AHP) of the multiple criteria decision analysis method is used to study the model. Through multi-criteria decision analysis, the evaluation index system of dynamic data acquisition technology of medical imaging equipment is constructed from aspects such as the reliability and traceability of data acquisition, the interactivity of the acquisition mode, and the extensibility of application analysis. A hierarchical evaluation model of dynamic acquisition technology for medical imaging equipment is constructed, which includes 5 primary indexes, 14 secondary indexes, and 38 tertiary indexes. We have constructed a qualitative and quantitative evaluation index for the dynamic acquisition technology of medical imaging equipment. The weight of the quantitative index "reliability" is 30%, and the weights of the qualitative indexes "security", "traceability", "interactivity", and "scalability" are 25%, 20%, 15%, and 10% respectively. It can be used to study the methods and technical characteristics of three kinds of dynamic data acquisition of medical equipment and form a technical evaluation scheme for dynamic data acquisition.

Evaluation method of modification effect of direct-to-plant SBS modifier on asphalt

To accurately evaluate the modification effect of direct-to-plant styrene–butadiene–styrene block copolymer (SBS) modifier on asphalt, a collection method for direct-to-plant SBS-modified asphalt was proposed in this paper, the qualitative and quantitative evaluation index system was established, and the feasibility of quantitative evaluation based on fluorescence microscopy images and visual inspection of the mixing effect was evaluated, the feasibility of quantitative evaluation indicators was also verified based on the asphalt indicators, rheological properties, and asphalt mixtures's pavement performances. The research results indicate that based on fluorescence microscopy images, by observing the distribution and swelling state of direct-to-plant SBS modifiers can qualitatively evaluate the modification effect of direct-to-plant SBS modifiers on asphalt. Based on the visual inspection of the mixing effect, observe the size and quantity of unmelted particles, determine the melting state of the direct-to-plant SBS modifier, and its modification effect on asphalt can be qualitatively evaluated. For the same direct-to-plant SBS-modified asphalt, the percentage of rotation viscosity between direct-to-plant SBS-modified asphalt and traditional SBS-modified asphalt at 135 ℃ (DAη(135℃)) and discrete coefficient of 135 ℃ rotational viscosity of direct-to-plant SBS-modified asphalt (CVη(135℃)) exhibit a linear relationship with direct-to-plant SBS-modified asphalt's penetration, softening point, and ductility, the smaller the CVη(135℃), the greater the DAη(135℃). The smaller the CVη(135℃) (the larger the DAη(135℃)), the larger the dynamic shear modulus (G*), the smaller the phase angle (δ), and the larger the rutting factor (G*/sinδ) at the same scanning temperature. The relationship between CVη(135℃) (DAη(135℃)) and direct-to-plant SBS modifier on the main technical indicators and rheological performance indicators of asphalt is relatively stable. There is a clear relationship between CVη(135℃) (DAη(135℃)) and the high-temperature stability, low-temperature crack resistance, and water stability of direct-to-plant SBS-modified asphalt mixture, all of which show that as CVη(135℃) decreases (DAη(135℃) increases), the pavement performances improve.

Construction and empirical research of the evaluation index system of environmental protection enterprises’ competitiveness based on the Delphi and AHP methods

Abstract The environmental protection industry has become an important support entity for the construction of ecological civilization and economic growth in China. However, there is little research on the competitiveness of environmental protection enterprises (EPEs). The construction of a set of scientific, comprehensive, practical, qualitative, and quantitative evaluation index systems is an important prerequisite for the sustainable and healthy development of the industry. Based on the literature analysis, semi-structured interviews with experts, and the Delphi method, the evaluation indicators for the competitiveness of EPEs were determined. Qualitatively, the evaluation index system of the competitiveness of EPEs contained 5 primary indicators, 12 secondary indicators, and 39 tertiary indicators. The analytic hierarchy process was used to determine the weights of indicators at each level. The primary indicators in order of weighting were organizational management capability, business environment, financial capability, innovation capability, and social responsibility, with corresponding weights of 26.13, 24.82, 21.76, 19.60, and 7.68%, respectively. Eight A-share listed EPEs in the water sector were selected for competitive evaluation. The evaluation index system of EPEs' competitiveness, being scientific-practical, combined, and quantitative, was constructed to provide a reference for the comprehensive evaluation of enterprises and the sustainable and healthy development of the industry.

Improved Neural Network with Spatial Pyramid Pooling and Online Datasets Preprocessing for Underwater Target Detection Based on Side Scan Sonar Imagery

Fast and high-accuracy detection of underwater targets based on side scan sonar images has great potential for marine fisheries, underwater security, marine mapping, underwater engineering and other applications. The following problems, however, must be addressed when using low-resolution side scan sonar images for underwater target detection: (1) the detection performance is limited due to the restriction on the input of multi-scale images; (2) the widely used deep learning algorithms have a low detection effect due to their complex convolution layer structures; (3) the detection performance is limited due to insufficient model complexity in training process; and (4) the number of samples is not enough because of the bad dataset preprocessing methods. To solve these problems, an improved neural network for underwater target detection—which is based on side scan sonar images and fully utilizes spatial pyramid pooling and online dataset preprocessing based on the You Look Only Once version three (YOLO V3) algorithm—is proposed. The methodology of the proposed approach is as follows: (1) the AlexNet, GoogleNet, VGGNet and the ResNet networks and an adopted YOLO V3 algorithm were the backbone networks. The structure of the YOLO V3 model is more mature and compact and has higher target detection accuracy and better detection efficiency than the other models; (2) spatial pyramid pooling was added at the end of the convolution layer to improve detection performance. Spatial pyramid pooling breaks the scale restrictions when inputting images to improve feature extraction because spatial pyramid pooling enables the backbone network to learn faster at high accuracy; and (3) online dataset preprocessing based on YOLO V3 with spatial pyramid pooling increases the number of samples and improves the complexity of the model to further improve detection process performance. Three-side scan imagery datasets were used for training and were tested in experiments. The quantitative evaluation using Accuracy, Recall, Precision, mAP and F1-Score metrics indicates that: for the AlexNet, GoogleNet, VGGNet and ResNet algorithms, when spatial pyramid pooling is added to their backbone networks, the average detection accuracy of the three sets of data was improved by 2%, 4%, 2% and 2%, respectively, as compared to their original formulations. Compared with the original YOLO V3 model, the proposed ODP+YOLO V3+SPP underwater target detection algorithm model has improved detection performance through the mAP qualitative evaluation index has increased by 6%, the Precision qualitative evaluation index has increased by 13%, and the detection efficiency has increased by 9.34%. These demonstrate that adding spatial pyramid pooling and online dataset preprocessing can improve the target detection accuracy of these commonly used algorithms. The proposed, improved neural network with spatial pyramid pooling and online dataset preprocessing based on the YOLO V3 method achieves the highest scores for underwater target detection results for sunken ships, fish flocks and seafloor topography, with mAP scores of 98%, 91% and 96% for the above three kinds of datasets, respectively.

Evaluating Sustainability of Tourism Projects in Rural Land Development Base on a Resilience Model

The underutilisation or overutilisation of various interdependent and interacting factors poses a challenge to sustainable development and requires the development of an appropriate methodology to evaluate the sustainability of tourism development projects in rural Land (TDPRL). However, most previous evaluations of TDPRL sustainability are macro-oriented and ignore the entire project life cycle. This study focuses on the resilience characteristics of TDPRL and proposes a “sustainable resilience model” based on physical-mechanical theory, which analyses various factors influencing TDPRL resilience based on the three dimensions of tractive force, driving force, and internal dynamic, and constructs a qualitative evaluation index system through stakeholder meetings. Then the analytic network process (ANP) is used to assess the resilience of TDPRL quantitatively. The rationality of the evaluation index system is validated through an empirical analysis of three rural tourism projects in Zhengzhou, Henan Province. We found that the resilience of TDPRL depends first on the project fundamentals, which include population, industry, location, and infrastructure. Second, local elites are crucial to rural tourism revitalization. Third, the project team should have sufficient capacity to provide tourists with satisfactory products and services, ensuring the project’s sustainable operation, and meeting the core demands of stakeholders. This study provides a novel tool for the decision-making and improvement of rural tourist project development and land use planning over the project life cycle.

Robust algorithm of indirect tyre pressure monitoring system based on tyre torsional resonance frequency analysis

• Detects changes in tyre pressure by monitoring changes in tyre resonance frequency. • Eliminating the disturbances of engine and driveline on frequency estimation. • Key parameters for evaluating tyre torsional vibration characteristics is proposed. • Methods proposed to compensate for the effects of road roughness and ambient temperature. • The proposed algorithm improves the robustness of frequency estimation. This paper focuses on an indirect Tyre Pressure Monitoring System (TPMS) algorithm based on frequency analysis of tyre torsional vibration. Tyre vibration is analysed using a tyre structure model, and the tyre resonance frequency is estimated using an Autoregressive (AR) model. The vibration disturbances from the engine and driveline that affect the estimation of the tyre torsional frequency are analysed, and a notch filter is designed to eliminate the disturbances. The torsional vibration of the driveline is identified by the correlation analysis of driving wheel speed. Two qualitative evaluation indexes of tyre torsional vibration characteristics are proposed. The corresponding quantitative parameters are used to determine the tyre torsional vibration state to eliminate the interference of undesirable vibration states on the frequency calculation. A road roughness estimation method is proposed based on tyre vertical vibration information in the wheel speed. The estimated road roughness parameters compensate for the calculated resonance frequency affected by road roughness. Based on the relationship between measured resonance frequency and temperature under a constant tyre pressure condition, the frequency variation value affected by tyre rubber stiffness variation due to temperature variation is calculated using the ambient temperature signal. The calculated resonance frequency is corrected to eliminate the coupling effect of gas stiffness and rubber stiffness, the impact of temperature variation on tyre pressure estimation is compensated. The results of vehicle road tests demonstrate the robustness of the proposed tyre pressure monitoring algorithm.

Prediction and optimization of gas distribution quality for high-temperature PEMFC based on data-driven surrogate model

Suitable operating conditions can improve the internal gas distribution of high-temperature proton exchange membrane fuel cell (HT-PEMFC), reduce the occurrence of local gas starvation, and thus prolong the lifespan. Therefore, it is important to investigate the gas distribution quality of HT-PEMFC based on quantitative indicators. In this paper, data-driven surrogate models are established based on the simulation results of a three-dimensional validated numerical model to study the gas distribution quality of HT-PEMFC via two qualitative evaluation indexes, the value of mean and standard deviation of the reactant gas concentration in catalyst layer. In order to obtain the surrogate model more efficiently and accurately, genetic algorithm optimized deep belief network (GA-DBN) and Autogluon (an automated machine learning method) are applied. Based on the surrogate models, the influence of the operating condition parameters on each evaluation index is revealed, which provides theoretical basis for the life-extension design of HT-PEMFC. Then, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), a Multi-Criteria Decision Aid (MCDA) method, is used to select the optimal operating conditions according to the two evaluation indexes of gas distribution quality from the extensive computational results of the surrogate models, which provides specific guidance for the life duration improvement of HT-PEMFC.

Feature Matching technology of Visible and Infrared Fusion Image based on VIFB

In view of the needs of all-time navigation tasks, visual navigation technology based on visible and infrared images has received extensive attention. At present, visible and infrared fusion technology is mostly used in remote sensing detection, target recognition and other fields, but it has not been widely used in the field of navigation and lacks a representative technology evaluation system. Therefore, a feature matching performance evaluation framework for visible and infrared fusion image based on the VIFB framework is proposed in this paper. A variety of typical indoor and outdoor target scenes are designed to test 20 visible and infrared image fusion algorithms. Then the ORB feature matching method is used to test the feature matching effect of image pairs before and after fusion. A variety of qualitative and quantitative evaluation indexes are designed to evaluate the VIFB framework. The feature matching performance of the images before and after processing is comprehensively evaluated. The experiments show that the fusion image can effectively deal with poor lighting and smoke occlusion. In various test scenarios, NSCT_SR, HMSD_GF and LatLRR algorithms show better feature matching performance, and CNN, MST_SR algorithms better integrate visible details and infrared salient structural information. The images fused by ADF, DLF, FPDE algorithms have good grayscale equalization effect.

Habitat Use and Niche Partitioning of Regina septemvittata and Nerodia sipedon in a Small Appalachian Stream in West Virginia

The common water snake, Nerodia sipedon, and the queen snake, Regina septemvittata are two species of stream-dwelling water snakes in the Family Natricidae native to the northern panhandle of West Virginia. Nerodia sipedon is a large-bodied generalist, ranging up to 140 cm in length and 400 g in mass, which feeds on many fish and amphibian species. Regina septemvittata is a smaller specialist, reaching only 92 cm in length and 100 g in mass, which primarily consumes freshly molted crayfish. In an ongoing study conducted by students at West Virginia University, I studied the habitat preferences of both of these species in the North fork of Short Creek as there has been little research done on habitat preferences in small streams. Morphological, environmental, and behavioral data on each snake that was captured. Qualitative habitat evaluation indexes (QHEI) were also collected to assess stream health in conjunction with presence and abundance of both species. No significant differences were found in the presence or abundance as it relates to QHEI, but trends show higher rates of presence and abundance in sites with lower QHEI scores. These results suggest that there is minimal interspecific competition of habitat present between N. sipedon and R. septemvittata, as well as support the hypothesis that both species thrive in more disturbed habitats.

The Microhabitat Preferences Based on Relative Density and Stream Assessment of Regina septemvittata in a small West Virginia Stream

Regina septemvittata is a slim-bodied water snake in the family Natricidae that is native to the northeastern United States. Being the only species to consume exclusively freshly molted crayfish, R. septemvittata is categorized as a specialist. The selectivity of prey suggests possible other narrow range preferences including refuge and hunting locations. This study is being conducted in the North Fork of Short Creek in Ohio County, WV. In addition, Nerodia sipedon sipedon is also found within the study stream system. N. s. Sipedon is a generalist water snake species that has been shown to be larger and more aggressive than R. septemvittata. Both species are captured throughout their activity period, April - November, starting in 2018. In addition to environmental and morphological data being recorded at the time of collection, qualitative habitat evaluation indexes (QHEI) were recorded at the initiation of the project. QHEI allows for a more standardized evaluation of the quality of the stream system. The combination of the quality of the stream in 100-meter sections of the stream in addition to snake location data can show relative preferences of R. septemvittata throughout the stream system. The current data suggests a greater preference for disturbed habitat as well as a higher frequency of hot spots in the stream as opposed to their generalist counterparts N. s. sipedon.

Robust total variation-based destriping model via sparse representation learning for business infrared imaging systems

Infrared images are often degraded by the issue of random and stripe noises in the business infrared focal plane imaging process. In this study, we proposed a novel infrared image destriping model with unidirectional and bidirectional total variation regularization. From the destriped infrared images, the stripe noise only exists in unidirection. The nature of unidirectional noise is leveraged to converted the total variation regularization and constructed the proposed model. For the random noise, the bidirectional total variation is introduced, which can preserve the image edge and texture details. Furthermore, the alternating direction method of multiplier algorithm is introduced to solve the infrared image destriping model. The proposed model is executed on several public infrared image datasets, thus outperforming the traditional destriping models in the qualitative evaluation index.

Remanufacturability evaluation method and application for used engineering machinery parts based on fuzzy-EAHP

Remanufacturing is an important mode to promote the sustainable development of manufacturing industry. Remanufacturing mechanical components at the best recycling time can effectively reduce the remanufacturing cost and improve the remanufacturing efficiency. Therefore, the decision-making model of optimal recycling time based on full lifecycle assessment and full lifecycle cost method was firstly established to analyze and model the energy consumption, cost and emission of components in the original manufacturing, usage, remanufacturing and reuse stages. Then, a remanufacturing evaluation method based on fuzzy extension analytic hierarchy process was proposed. Considering a variety of uncertainties of waste components, a qualitative and quantitative evaluation index system was established, and the weight of each evaluation index was determined by expert evaluation and fuzzy comprehensive evaluation method. Finally, a boom cylinder of a concrete pump truck was studied. The boom cylinder recovered by the method proposed has a high recovery value, and its comprehensive score reaches 70, which verifies the effectiveness and superiority of the model.

Feasibility Analysis of PPP Mode of Port Construction Based on the Whole Life Cycle

Li, X.; Wen, J.; You, Z., and Wang, Y., 2020. Feasibility analysis of PPP mode of port construction based on the whole life cycle. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 556–560. Coconut Creek (Florida), ISSN 0749-0208.With the development of international trade, as a transportation hub, ports play a more and more important role in the economic system, and then brings a lot of port development and construction including port over development, ecological damage and other issues, which gradually appear. The construction of ecological port provides solutions to these problems, so this essay analyzes the feasibility of PPP port construction in the whole life cycle, and compares the value for money of this development mode and the traditional mode. On the basis of reading a large number of domestic and foreign related literature, this essay explains the relevant theories and establishes the value for money evaluation model of ecological port construction under PPP mode. According to the needs of the whole life cycle construction of ecological port, qualitative evaluation indexes are selected, and evaluation standards are constructed for qualitative analysis. After qualitative analysis, the feasibility of the scheme is verified again by using the quantitative analysis model of value for money. The empirical analysis shows that in Q port, the construction of ecological port with PPP mode can achieve value for money. This essay not only establishes the value for money evaluation model of ecological port PPP mode construction from the perspective of the whole life cycle, improving the efficiency of Q port PPP mode construction, and Q port ecological environment and industrial environment, in order to promote port economic development, but also provides support for the sustainable development of PPP mode in China, resulting in providing reference for similar port construction.

Experimental study on the sensitive parameters of non-destructive test method for the cable based on the leakage magnetic principle

The nondestructive testing (NDT) technique of steel rope based on the leakage magnetic principle has been extensively applied to the cable. In view of the difference of geometric characteristics, structures, loading between steel rope and cable, the applicability of the leakage magnetic NDT and the sensitive parameters on detection accuracy should be studied. So a cable specimen with local defects was designed and fabricated, and then the leakage magnetic testing technique was applied. The experimental electrical signal output of the cable were compared and analyzed. The results show that the accuracy of the test results is strictly related to the geometric characteristics of the test instrument, the depth of internal defects, the height of sensor removal, the sensitivity coefficient of the magnetically sensitive element, the defect spacing, etc., and the qualitative evaluation and individual quantitative index of the cable defects are proposed. The above conclusions can provide data support for the test quantitative index and the application of nondestructive testing technique.

Stem Water Content for Crape Myrtle in Response to Drought, Cold, and Disease Stress

The abiotic and biotic stresses including drought, cold, and disease stress are linked by the fact that they all decrease the availability of water to plant cells. In previous studies, some physiological factors related with plant water status, such as stem sap flow, leaf transpiration rate, and water potential, were used to assess the effects of these stresses on plants. But there are few studies about the effects of these stresses on stem water content (StWC) which can be measured by a novel SWR sensor. In this study, crape myrtle was selected as an experimental subject and its StWC was observed in four experiments including no stress, drought, cold, and disease stress. Before conducting stress experiments, the StWC and environmental and physiological parameters were synchronously monitored under unstressed conditions on a typical day in summer. In the experiment of drought stress, the StWC was monitored under different gradients of soil moisture. In the experiment of cold stress, the StWC was monitored in warm and cold weather, respectively. In the experiment of disease stress, the StWC was monitored under different frequencies of disease treatment. The results showed that the correlation coefficients between StWC and PAR and VPD were larger than 0.5 and the correlation coefficients between StWC and Pn, Tr, Gs, and Ci were larger than 0.8 under no stress. The diurnal mean of StWC decreased firstly, then remained stable for a period of time, and eventually continued to fall under drought stress. On the whole, there was a negative correlation between the diurnal mean of StWC and the degree of drought stress. The StWC showed opposite diurnal variation rules in warm and cold weather. There was a positive correlation between the diurnal range of StWC and the degree of cold stress. The diurnal minimum, maximum, and mean of StWC showed a positive correlation with the health level of plants and the diurnal range of StWC showed a negative correlation with the health level of plants. In conclusion, the StWC can be used as a qualitative evaluation index of the degree of the three types of stress.

Study on Qualitative Evaluation Index System of VFM in PPP Project

With the vigorous development of PPP mode in China, the qualitative evaluation of value for money (VFM) has become an important support for the decision-making of PPP project. As the evaluation system of VFM is still not mature enough in China, it needs to be further improved. On the basis of the "Guide to VFM evaluation in PPP Project (trial)", to get further supplement and enrich the indicators of qualitative evaluation of PPP projects, and giving the specific judgment criterion, the expert investigation method and hierarchical analysis method are used to determine the weight of evaluation indexes, and then a qualitative evaluation model of VFM evaluation with strong operability and reasonable evaluation would be constructed. Finally, the model which is constructed in this paper would be tested by engineering projects so as to make the qualitative evaluation method scientific and feasible for PPP model.

Risk evaluation for the navigation environment of the LNG ship based on the cloud model

In order to enhance water transport safety of the LNG ship and improve the objectivity of risk assessment of LNG ships navigation environment, the cloud model which can realize the conversion between qualitative and quantitative evaluation indexes is used to evaluate the LNG ships navigation environment. Combined with the Delphi method, cloud weight and cloud model of indexes at all levels in the evaluation system are determined. At the same time, simulation is carried out by MATLAB software and cloud chart is obtained. And then we analyze the risk level of different factors in LNG ships navigation environment to get the evaluation results, which provides decision-making basis for navigation safety management. Overall, it is testified that the cloud model can reduce the randomness and fuzziness in the process of evaluating and the irrationality caused by the subjective assumption of weight distribution, which makes the results more reasonable and credible.

Risk assessment of rockburst via an extended MABAC method under fuzzy environment

The rockburst is a severe underground geological disaster, which has great damage to the workers, equipments and engineering structures. This paper aims to find a suitable way to assess the risk of rockburst within complicated decision making circumstances. First, plenty of literature related to the risk assessment indexes and methods of rockburst is reviewed. On account of the specific characteristics of rockburst, both quantitative and qualitative evaluation indexes are recognized in this paper. Owing to the fuzziness of human thinking and the complexity of risk assessment problems, triangular fuzzy numbers (TFNs) are advised to describe these indexes values. Meanwhile, the superiority linguistic ratings of decision makers (DMs) are used to determine the weights of indexes. After that, an extended multi-attributive border approximation area comparison (MABAC) method corresponding to TFNs is put forward to obtain the ranking results and specific risk levels of rockburst under fuzzy environment. Finally, an example of assessing the risk of rockburst in Kaiyang phosphate mine is illustrated. The rockburst proneness of four crucial areas is evaluated with the proposed method, and the ranking result is consistent with the field status. Besides, the effectiveness of this method is demonstrated with parameter and comparison analyses. The results show that the extended MABAC method is reliable and effective for evaluating the risk of rockburst, and provides references for the prevention and management of rockburst.

Research on the Hybrid ANP-FCE Approach of Urban Community Sustainable Construction Problem

As an important component of urban construction, the development of the community is of great significance to the sustainable construction of the entire society. The previous studies mainly focused on quantitative research and were limited by the data collectability, affecting the scientificity of the index system. Therefore, based on the theory of sustainable development, through the review of previous literature, combined with relevant experts' opinions and community development goals and other factors, a qualitative evaluation index system for community sustainable development capacity was established. The ANP (analytic network process) method is mainly used to determine the weight of each indicator, and FCE (fuzzy comprehensive evaluation) is proposed to determine every indicator’s membership. Then the hybrid fuzzy evaluation is promoted to evaluate the selected community as the empirical study. In this paper, the indicator selection is not limited by objective factors, and the evaluation system is more accurate; the application of ANP method makes the results of weight more scientific; meanwhile, fuzzy comprehensive evaluation can be suitable for solving various nondeterministic problems. This study transforms qualitative research into quantitative research; it provides an effective evaluation method for local managers and decision makers to carry out community sustainable construction.