Journal of Risk Analysis and Crisis Response Vol. 9(2), June (2019), pp. 93-100 DOI: https://doi.org/10.2991/jracr.k.190703.005; eISSN: 2210-8505, ISSN: 2210-8491 https://www.atlantis-press.com/journals/jracr © 2019, The Authors. Published by Atlantis Press SARL. This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/). Evaluation on Ecological Civilization Construction Level in Guizhou Based on Intuitionistic Fuzzy Analytic Hierarchy Process Xinpu Wang1,*, Mu Zang2, † 1. College of Big Data Application and Economics, Guizhou University of Finance and Economics Huaxi Guiyang Guizhou, China 2. College of Big Data Application and Economics, Guizhou University of Finance and Economics Huaxi Guiyang Guizhou, China Received January 7, 2019 Accepted March 4, 2019 Abstract In order to better build the ecological environment of Guizhou province, accelerate the marketization and capitalization of Guizhou province's ecological resources, and evaluate and study the construction level of Guizhou's ecological civilization. This paper, by using IFAHP, the establishment of intuitionistic fuzzy judgment matrix, consistency test, calculate the nine-province each secondary index to the weight of a layer and target layer, the comprehensive evaluation value is calculated and sorted. The empirical research shows that the ecological civilization construction level of Guizhou province is relatively high, but the level distribution of all prefectures and cities is very uneven, and the difference between the highest score southeast Guizhou and the lowest score Liupanshui is 4.87. Therefore, it is necessary to accelerate the construction of ecological civilization in various prefectures and cities, so as to improve the construction level of ecological civilization in the whole province and promote regional economic development. Keywords: construction of ecological civilization; the level of ecological civilization construction; IFAHP; comprehensive evaluation *Guizhou University of Finance and Economics, Huaxi Guiyang Guizhou 550025, China. †Corresponding author: rim_007@163.com 1. Introduction At the Fifth Plenary Session of the Eighteenth Central Committee of the Communist Party of China, the development concept of "innovation, coordination, green, open and sharing" was put forward, which put forward higher requirements for the construction of ecological civilization. The construction of ecological civilization is of great significance to solve the resource and environment problems facing our country. "Green water and green hills are Jinshan and Yinshan". Green development has become the theme of China's economic and social development in the 13th Five-Year Plan period and even in the longer term. The key to building a resource-saving and environment-friendly society lies in the improvement of ecological environment, which plays an important role in promoting economic growth and industrial upgrading, promoting energy conservation and emission reduction, protecting the environment and improving ecological efficiency. Guizhou, as a national experimental area of ecological civilization, Guian New Area is the first batch in China and the only national experimental area in southwest China to be allowed to carry out green financial reform and innovation. Firstly, the improvement of the level of ecological civilization construction plays a positive role in promoting the marketization and capitalization of ecological resources in Guizhou. Focusing on the three strategies of poverty Journal of Risk Analysis and Crisis Response Vol. 9, No. 2 (June 2019) 93-100 94 alleviation, big data and big ecology, Guizhou will focus on developing the "four-type" industries, which will bring huge investment opportunities and financial needs, provide support for Guizhou's ecological construction, and promote the realization of the "three orientations" in the new area. Finally, it will be conducive to fostering new momentum of economic development and providing loans for regional economic development. This paper uses intuitionistic fuzzy analytic hierarchy process (IFAHP) to comprehensively evaluate the level of ecological civilization construction in nine cities and municipalities of Guizhou and to provide development suggestions for improving the level of ecological civilization construction in Guizhou Province. 2. An overview of domestic and foreign research With the improvement of environmental awareness, great progress has been made in the evaluation of the level of ecological civilization construction. Early scholar Zhao Fang (2010) [1] decomposed the evaluation index of ecological civilization construction into four core areas: production mode, lifestyle, ecological protection and construction, social development, and set up several specific indicators, and constructed a three- level, 27 single evaluation index structure from "target level-criterion level-index level". The evaluation index system of ecological civilization construction was established, and the progress rate analysis method was used to evaluate the construction of ecological civilization. In recent years, Zhang Huan et al. (2015) [2] has established an evaluation index system of ecological civilization in mega-cities, which includes four aspects: the degree of ecological environment health, the intensity of resource and environment consumption, the efficiency of non-point source pollution control and the livability of residents, with a total of 20 indicators, and put forward measures to strengthen the construction of ecological civilization. Zheng Yanling et al. (2016) [3] Taking Hebei Province as an example, this paper constructs a comprehensive evaluation index system of ecological civilization construction and regional economic development level, adopts the measurement model of ecological civilization construction and regional economic coordinated development, and puts forward that with the advancement of ecological civilization construction, the relationship between ecological civilization and economic development will enter into mutual complementarity. Good circulation. Cheng Jinhua et al. (2018) [4] Taking 35 provincial capitals and sub-provincial cities in China and 7 small and medium-sized cities in Hubei Province as objects, the index system is constructed from four dimensions: land and space optimization, resource and energy utilization, ecological environment protection and governance, and ecological system construction. The index weight is given by the method of entropy weight. Empirical research finds that big cities are the main cities. Cities with a high index of ecological civilization often have the characteristics of balanced development of the economy and environment. There are few studies on the evaluation of Guizhou's ecological civilization construction, and more qualitative analysis is used to analyze the current situation of Guizhou's ecological civilization construction (Jiangchuan et al. [5], 2014; Shipeixin [6], 2010, etc.). Van Laarhoven and Edrycz (1983) [7] proposed for the first time to fuzzify the analytic hierarchy process (AHP). Buckley (1985) [8] developed the fuzzy analytic hierarchy process (FAHP) on this basis. It is more complete and accurate to evaluate the target level indicators, which can reflect the uncertainty of the decision-makers in the evaluation of objective things. The subjectivity of experts is fuzzified, which is more objective and accurate than the analytic hierarchy process, but it can not accurately express the situation of abstention or hesitation, and the quantitative and qualitative indicators need to be aggregated by different methods. In order to solve this problem, an intuitionistic fuzzy analytic hierarchy process (IFAHP) based on the concept of fuzzy sets is proposed, which unifies the aggregation of qualitative and quantitative indicators. Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) has also been widely used in the field of a comprehensive evaluation in China, and the effectiveness of this method has been proved [9]. For example, Gu Jing et al. (2015) [10] used the intuitionistic fuzzy analytic hierarchy process to evaluate the performance of venture capital guiding fund. Compared with the traditional fuzzy analytic hierarchy process, it was found that this method has better performance in the evaluation accuracy. Zhang Shang-wai (2016) [11] put forward that the intuitionistic fuzzy analytic hierarchy process (IFAHP) should be used to evaluate the operation status of power grid scientifically and reasonably and to rank the comprehensive evaluation Journal of Risk Analysis and Crisis Response Vol. 9, No. 2 (June 2019) 93-100 94 95 alleviation, big data and big ecology, Guizhou will focus on developing the "four-type" industries, which will bring huge investment opportunities and financial needs, provide support for Guizhou's ecological construction, and promote the realization of the "three orientations" in the new area. Finally, it will be conducive to fostering new momentum of economic development and providing loans for regional economic development. This paper uses intuitionistic fuzzy analytic hierarchy process (IFAHP) to comprehensively evaluate the level of ecological civilization construction in nine cities and municipalities of Guizhou and to provide development suggestions for improving the level of ecological civilization construction in Guizhou Province. 2. An overview of domestic and foreign research With the improvement of environmental awareness, great progress has been made in the evaluation of the level of ecological civilization construction. Early scholar Zhao Fang (2010) [1] decomposed the evaluation index of ecological civilization construction into four core areas: production mode, lifestyle, ecological protection and construction, social development, and set up several specific indicators, and constructed a three- level, 27 single evaluation index structure from "target level-criterion level-index level". The evaluation index system of ecological civilization construction was established, and the progress rate analysis method was used to evaluate the construction of ecological civilization. In recent years, Zhang Huan et al. (2015) [2] has established an evaluation index system of ecological civilization in mega-cities, which includes four aspects: the degree of ecological environment health, the intensity of resource and environment consumption, the efficiency of non-point source pollution control and the livability of residents, with a total of 20 indicators, and put forward measures to strengthen the construction of ecological civilization. Zheng Yanling et al. (2016) [3] Taking Hebei Province as an example, this paper constructs a comprehensive evaluation index system of ecological civilization construction and regional economic development level, adopts the measurement model of ecological civilization construction and regional economic coordinated development, and puts forward that with the advancement of ecological civilization construction, the relationship between ecological civilization and economic development will enter into mutual complementarity. Good circulation. Cheng Jinhua et al. (2018) [4] Taking 35 provincial capitals and sub-provincial cities in China and 7 small and medium-sized cities in Hubei Province as objects, the index system is constructed from four dimensions: land and space optimization, resource and energy utilization, ecological environment protection and governance, and ecological system construction. The index weight is given by the method of entropy weight. Empirical research finds that big cities are the main cities. Cities with a high index of ecological civilization often have the characteristics of balanced development of the economy and environment. There are few studies on the evaluation of Guizhou's ecological civilization construction, and more qualitative analysis is used to analyze the current situation of Guizhou's ecological civilization construction (Jiangchuan et al. [5], 2014; Shipeixin [6], 2010, etc.). Van Laarhoven and Edrycz (1983) [7] proposed for the first time to fuzzify the analytic hierarchy process (AHP). Buckley (1985) [8] developed the fuzzy analytic hierarchy process (FAHP) on this basis. It is more complete and accurate to evaluate the target level indicators, which can reflect the uncertainty of the decision-makers in the evaluation of objective things. The subjectivity of experts is fuzzified, which is more objective and accurate than the analytic hierarchy process, but it can not accurately express the situation of abstention or hesitation, and the quantitative and qualitative indicators need to be aggregated by different methods. In order to solve this problem, an intuitionistic fuzzy analytic hierarchy process (IFAHP) based on the concept of fuzzy sets is proposed, which unifies the aggregation of qualitative and quantitative indicators. Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) has also been widely used in the field of a comprehensive evaluation in China, and the effectiveness of this method has been proved [9]. For example, Gu Jing et al. (2015) [10] used the intuitionistic fuzzy analytic hierarchy process to evaluate the performance of venture capital guiding fund. Compared with the traditional fuzzy analytic hierarchy process, it was found that this method has better performance in the evaluation accuracy. Zhang Shang-wai (2016) [11] put forward that the intuitionistic fuzzy analytic hierarchy process (IFAHP) should be used to evaluate the operation status of power grid scientifically and reasonably and to rank the comprehensive evaluation values, which is of great significance for the prevention of major blackouts. In view of this, on the basis of previous studies, this paper establishes an index system including four primary indicators: ecological economy, ecological environment, ecological livability and ecological culture, and then evaluates the level of ecological civilization construction in nine cities and municipalities of Guizhou Province by using intuitionistic fuzzy analytic hierarchy process. 3. Establishment of an index system of Ecological Civilization Construction Level The selection of ecological civilization indicators plays an important role in accurately evaluating the level of ecological civilization construction. This paper follows the principles of comprehensiveness and representativeness, pertinence and comparability, orientation and foresight when constructing the index system. It emphasizes the sustainable development of nature, environment, human and society, and takes into account the carrying capacity of ecological environment, to promote the harmonious development of human and nature on the basis of improving social-ecological civilization. Reference [12], four first-level indicators and 23 second-level indicators were developed, such as Table 1. T he d ata so urces o f p aper : China Regio nal Economic Statistics Yearbook, Guizhou Statistical Yearbook, Nine Prefecture, and City Statis tical Yearbooks, Prefecture and City Water Resources Bulletin, Environment Bulletin and National Economic Development Bulletin. Among them, the per capita housing area of Anshun, southeastern Guizhou and southwestern Guizhou is estimated by the data of past years; the proportion of added value of cultural industry in GDP in Anshun, Zunyi, and Bijie, and the per capita green area of parks in southwestern Guizhou are estimated by the government's press announcement, and the sulfur dioxide emissions and industrial solid waste synthesis in southern Guizhou are estimated. Utilization ratio, the proportion of added value of cultural industry to GDP, average temperature and annual precipitation all come from the official website of the state government; the comprehensive utilization ratio of industrial solid waste in Tongren City, the per capita green space area of parks in southeastern Guizhou and southern Guizhou and the proportion of added value of Table 1. Evaluation Index System of Ecological Civilization Construction Level in Guizhou. First level index Two level index Eco economy A1 Per capita gross domestic product(RMB) B1 The growth rate of the added value of the tertiary industry as a proportion of GDP (%) B2 Per capita growth rate of general public budget income (%) B3 Energy Consumption per Unit GDP(Ton of Standard Coal/10000 Yuan) B4 Power consumption per unit GDP (kWh/10000 yuan) B5 General Public Budget Expenditure - Energy Conservation and Environmental Protection (RMB 10,000) B6 Ecological environment A2 Forest cover (%) B7 Excellent rate of urban ambient air quality (%) B8 Water quality of centralized drinking water sources above county level (%) B9 Increase rate of fertilizer application for agriculture (%) B10 Comprehensive Utilization Rate of Industrial Solid Waste (%) B11 Total sulphur dioxide emissions (10,000 tons) B12 Ecological livability A3 Per capita park green space area (square metre/person) B13 Harmless disposal rate of municipal solid waste (%) B14 Average temperature (。C) B15 Annual precipitation (mm) B16 Per capita highway mileage (km) B17 Per capita housing area in urban areas (square meters) B18 Ecological culture A4 General Public Budget Expenditure - Education Services (RMB 100 million) B19 General Public Budget Expenditure - Culture, Sports and Media (RMB 100 million) B20 The proportion of the added value of the cultural industry to GDP (%) B21 Students in Higher Education (Persons) B22 Students in Ordinary Secondary Schools (Persons) B23 cultural industry in GDP in southeastern Guizhou and southwestern Guizhou are estimated by the government's news bulletins. 4. Models and Methods 4.1 Standardization of Data According to the attributes of the indicators, the indicators in this paper can be divided into benefit type, Journal of Risk Analysis and Crisis Response Vol. 9, No. 2 (June 2019) 93-100 96 cost type, and medium type. Benefit-oriented indicators refer to the indicators with bigger values, while cost- oriented indicators refer to the indicators with smaller values. For benefit, cost and medium-sized indicators, the standardization methods [13] are: Among them, i = 1, 2,..., m, m is the number of evaluation objects; j= 1, 2,..., n, n is the number of attributes, *, ,max min-j ij j ij jx x x x x   is the best stable value of j index. After data standardization, the values measured by various attributes change from 0 to 1. 4.2 Comprehensive assessment Steps Atanassov further extends the theory of fuzzy sets proposed by Zadeh and defines intuitionistic fuzzy sets. Recently, intuitionistic fuzzy set theory has been widely used in decision-making field. The comprehensive assessment Steps of IFAHP are as follows: The First Step: Determine the index system. This paper constructs the index system of ecological civilization construction from four perspectives of ecological economy, ecological environment, ecological livability, and ecological culture, as shown in Table 1. The Second Step: Establish an intuitionistic fuzzy judgment matrix. This paper compares the importance of each factor of the same level index to a certain index of the upper level in two ways. Through expert scoring, an intuitionistic fuzzy judgment matrix  ij n nR R  , ji, is established to represent the rows and columns of the intuitionistic fuzzy judgment matrix, in which ),(ij ijij vuR  and iju represent the membership degree, i.e., the degree of superiority of index i to index j , ijv denotes non-membership, i.e. the degree of inferiority of index i to index j , and ij denotes hesitation, ijijij vu 1 . The correspondence between qualitative evaluations and intuitionistic fuzzy numbers is shown in Table 2. Step 3: Consistency test. The consistency test of the intuitive judgment matrix is carried out. If consistency is satisfied, jump to Step 5; otherwise, move to Step 4. Using the test formula Table 2. Correspondence tables between qualitative evaluations and intuitionistic fuzzy numbers. Qualitative evaluation language Intuitionistic fuzzy number Qualitative evaluation language Intuitionistic fuzzy number Extremely important (0.90,0.10,0.00) Less important (0.4,0.45,0.15) Very important (0.80,0.15,0.05) Unimportant (0.30,0.60,0.10) Important (0.70,0.20,0.10) Not important (0.20,0.75,0.05) More important (0.60,0.25,0.15) Extremely unimportant (0.10,0.90,0.00) Equally important (0.50,0.30,0.20) _ _       n i n j ijijijijij vvuu nn RRd 1 1 ij )( )2)(1(2 1 ),( ππ R is an intuitionistic fuzzy judgment matrix and an intuitionistic fuzzy consistency judgment matrix,  ij n nR R  . (1)When j>i+1, ( ) ( , )ij ij ijR r u v  ; (2)When j=i + 1, order ij ijr r ; (3)When ji+1, ( ) ( , )ij ij ijR r u v  ; (2)When j=i + 1, order ij ijr r ; (3)When j 00.1, which did not pass the consistency test. Therefore, it can be said that the above table is not an intuitionistic fuzzy consistency judgment matrix. The calculation method and process of the other matrices are the same. The Step 7 is used to calculate the comprehensive evaluation values of nine prefectures and cities, and the Journal of Risk Analysis and Crisis Response Vol. 9, No. 2 (June 2019) 93-100 98 Table 3. Intuitionistic Fuzzy Judgment Matrix. B7 B8 B9 B10 B11 B12 B7 (0.5,0.5) (0.25,0.6) (0.8,0.15) (0.8,0.15) (0.7,0.2) (0.6,0.25) B8 (0.6,0.25) (0.5,0.5) (0.8,0.15) (0.9,0.1) (0.8,0.15) (0.7,0.2) B9 (0.15,0.8) (0.15,0.8) (0.5,0.5) (0.25,0.6) (0.25,0.6) (0.2,0.7) Table 4. Intuitionistic Fuzzy Consistency Judgment Matrix. B7 B8 B9 B10 B11 B12 B7 (0.5,0.5) (0.25,0.6) (0.57,0.2) (0.67,0.17) (0.72,0.13) (0.49,0.28) B8 (0.6,0.25) (0.5,0.5) (0.8,0.15) (0.57,0.2) (0.8,0.08) (0.62,0.23) B9 (0.2,0.57) (0.15,0.8) (0.5,0.5) (0.25,0.6) (0.44,0.27) (0.1,0.73) B10 (0.17,0.67) (0.2,0.57) (0.6,0.25) (0.5,0.5) (0.7,0.2) (0.61,0.17) B11 (0.13,0.72) (0.08,0.8) (0.27,0.44) (0.2,0.7) (0.5,0.5) (0.4,0.45) B12 (0.28,0.49) (0.23,0.62) (0.73,0.1) (0.17,0.61) (0.45,0.4) (0.5,0.5) Table 5. Intuitionistic Fuzzy Consistency Judgment Matrix. B7 B8 B9 B10 B11 B12 B7 (0.5,0.5) (0.25,0.6) (0.75,0.16) (0.77,0.15) (0.71,0.,18) (0.57,0.26) B8 (0.6,0.25) (0.5,0.5) (0.8,0.15) (0.85,0.12) (0.80,0.13) (0.68,0.21) B9 (0.16,0.75) (0.15,0.8) (0.5,0.5) (0.25,0.6) (0.29,0.51) (0.17,0.71) B10 (0.15,0.77) (0.12,0.85) (0.6,0.25) (0.5,0.5) (0.7,0.2) (0.23,0.66) B11 (0.18,0.71) (0.13,0.80) (0.51,0.29) (0.2,0.7) (0.5,0.5) (0.4,0.45) B12 (0.26,0.57) (0.21,0.68) (0.71,0.17) (0.66,0.23) (0.45,0.4) (0.5,0.5) Table 6. Total Weight Tables of Indicators. First level index weight Two level index weight Total weight First level index weight Two level index weight Total weight (0.137,0.785) (0.092,0.832) (0.013,0.964) (0.237,0.676) (0.137,0.795) (0.033,0.934) (0.144,0.772) (0.020,0.951) (0.137,0.805) (0.032,0.937) (0.081,0.868) (0.011,0.972) (0.229,0.712) (0.054,0.907) (0.187,0.729) (0.026,0.942) (0.186,0.754) (0.044,0.920) (0.105,0.818) (0.014,0.961) (0.040,0.891) (0.010,0.965) (0.185,0.722) (0.025,0.940) (0.088,0.867) (0.021,0.957) (0.324,0.587) (0.180,0.746) (0.058,0.895) (0.149,0.772) (0.142,0.754) (0.021,0.944) (0.215,0.716) (0.070,0.883) (0.159,0.740) (0.024,0.941) (0.077,0.869) (0.025,0.946) (0.222,0.662) (0.033,0.923) (0.117,0.830) (0.038,0.930) (0.141,0.747) (0.021,0.942) (0.098,0.844) (0.032,0.935) (0.105,0.797) (0.016,0.954) (0.142,0.788) (0.046,0.913) Journal of Risk Analysis and Crisis Response Vol. 9, No. 2 (June 2019) 93-100 98 99 Table 3. Intuitionistic Fuzzy Judgment Matrix. B7 B8 B9 B10 B11 B12 B7 (0.5,0.5) (0.25,0.6) (0.8,0.15) (0.8,0.15) (0.7,0.2) (0.6,0.25) B8 (0.6,0.25) (0.5,0.5) (0.8,0.15) (0.9,0.1) (0.8,0.15) (0.7,0.2) B9 (0.15,0.8) (0.15,0.8) (0.5,0.5) (0.25,0.6) (0.25,0.6) (0.2,0.7) Table 4. Intuitionistic Fuzzy Consistency Judgment Matrix. B7 B8 B9 B10 B11 B12 B7 (0.5,0.5) (0.25,0.6) (0.57,0.2) (0.67,0.17) (0.72,0.13) (0.49,0.28) B8 (0.6,0.25) (0.5,0.5) (0.8,0.15) (0.57,0.2) (0.8,0.08) (0.62,0.23) B9 (0.2,0.57) (0.15,0.8) (0.5,0.5) (0.25,0.6) (0.44,0.27) (0.1,0.73) B10 (0.17,0.67) (0.2,0.57) (0.6,0.25) (0.5,0.5) (0.7,0.2) (0.61,0.17) B11 (0.13,0.72) (0.08,0.8) (0.27,0.44) (0.2,0.7) (0.5,0.5) (0.4,0.45) B12 (0.28,0.49) (0.23,0.62) (0.73,0.1) (0.17,0.61) (0.45,0.4) (0.5,0.5) Table 5. Intuitionistic Fuzzy Consistency Judgment Matrix. B7 B8 B9 B10 B11 B12 B7 (0.5,0.5) (0.25,0.6) (0.75,0.16) (0.77,0.15) (0.71,0.,18) (0.57,0.26) B8 (0.6,0.25) (0.5,0.5) (0.8,0.15) (0.85,0.12) (0.80,0.13) (0.68,0.21) B9 (0.16,0.75) (0.15,0.8) (0.5,0.5) (0.25,0.6) (0.29,0.51) (0.17,0.71) B10 (0.15,0.77) (0.12,0.85) (0.6,0.25) (0.5,0.5) (0.7,0.2) (0.23,0.66) B11 (0.18,0.71) (0.13,0.80) (0.51,0.29) (0.2,0.7) (0.5,0.5) (0.4,0.45) B12 (0.26,0.57) (0.21,0.68) (0.71,0.17) (0.66,0.23) (0.45,0.4) (0.5,0.5) Table 6. Total Weight Tables of Indicators. First level index weight Two level index weight Total weight First level index weight Two level index weight Total weight (0.137,0.785) (0.092,0.832) (0.013,0.964) (0.237,0.676) (0.137,0.795) (0.033,0.934) (0.144,0.772) (0.020,0.951) (0.137,0.805) (0.032,0.937) (0.081,0.868) (0.011,0.972) (0.229,0.712) (0.054,0.907) (0.187,0.729) (0.026,0.942) (0.186,0.754) (0.044,0.920) (0.105,0.818) (0.014,0.961) (0.040,0.891) (0.010,0.965) (0.185,0.722) (0.025,0.940) (0.088,0.867) (0.021,0.957) (0.324,0.587) (0.180,0.746) (0.058,0.895) (0.149,0.772) (0.142,0.754) (0.021,0.944) (0.215,0.716) (0.070,0.883) (0.159,0.740) (0.024,0.941) (0.077,0.869) (0.025,0.946) (0.222,0.662) (0.033,0.923) (0.117,0.830) (0.038,0.930) (0.141,0.747) (0.021,0.942) (0.098,0.844) (0.032,0.935) (0.105,0.797) (0.016,0.954) (0.142,0.788) (0.046,0.913) ranking results are shown in Table 7, where the comprehensive evaluation value of southeastern Guizhou is 12.72, with the highest score, followed by Guiyang, southern Guizhou, southwestern Guizhou, Tongren, and Zunyi, with 11.94, 11.88, 11.42, 10.97 and 10.72 respectively. Bijie, Anshun and Liupanshui scored lower, 9.72, 9.55 and 7.81 respectively. The construction level of ecological civilization in nine cities and municipalities is relatively high, but the development level is unbalanced. Table 7. Ranking table of comprehensive evaluation results. Region Comprehensive evaluation value Sort Qiandongnan 12.72 1 Guiyang 11.94 2 Qiannan 11.88 3 Qianxinan 11.42 4 Tongren 10.97 5 Zunyi 10.72 6 Bijie 9.72 7 Anshun 9.55 8 Liupanshui 7.81 9 6. Conclusion This paper applies the intuitionistic fuzzy analytic hierarchy process (IFAHP) to evaluate the level of ecological civilization construction in Guizhou Province and establishes an index system including four first- level indicators of the ecological economy, ecological environment, ecological livability and ecological culture, and 23 second-level indicators. The index weights are expressed by the intuitionistic fuzzy numbers, and then the scores are calculated and compared. However, limited by the statistical data of each prefecture and city, the representative of individual indicators is not strong. The empirical study of this paper shows that the level of ecological civilization construction in Guizhou Province is relatively high, but the level of each prefecture is quite different. Therefore, it is necessary for the governments, environmental protection bureaus and water conservancy bureaus of various prefectures and municipalities in Guizhou Province to take measures to further improve the ecological quality. For example, Guizhou Province should make full use of ecological resources, promote the marketization and capitalization of ecological resources in Guizhou Province, and respond to the national strategy to achieve green development, improve the efficiency of clean energy use, improve citizens'awareness of environmental protection, and increase the penalties for excessive pollutants discharged by industrial enterprises. 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