Fuzzy Mathematics Method Research Articles

Screening of fermentation resources of Actinidia arguta wine based on principal component analysis combined with a fuzzy mathematical sensory evaluation method

Screening of fermentation resources of Actinidia arguta wine based on principal component analysis combined with a fuzzy mathematical sensory evaluation method

Methods of Multi-Criteria Optimization of Technological Processes in a Fuzzy Environment Based on the Simplex Method and the Theory of Fuzzy Sets

Many modern technological objects in practice are characterized by the uncertainty of the initial information necessary for their management. Recently, one of the pressing scientific and practical problems is the development of new optimization methods for controlling the operating modes of such objects in a fuzzy environment. In this regard, the objective of this study is to develop methods of multi-criteria optimization in a fuzzy environment by modifying the simplex method and various optimality principles based on fuzzy mathematics methods. The methodology of the proposed study is based on a hybrid approach, which consists of the integrated use and modification of simplex methods and optimization methods with various optimality principles for working in a fuzzy environment. The main results are as follows: a simplex method of multi-criteria optimization of immeasurable criteria (here, we are talking about the impossibility of physical measurements of criteria, the values of which are estimated by decision maker); a theorem on the convergence of the solution sequence obtained using the proposed method to the minimum value of the criteria; a heuristic method based on a modification for fuzziness and a combination of the maximin and Pareto optimality principles, which allows effectively solving multi-criteria optimization problems in a fuzzy environment. The heuristic method proposed will be used to solve a real production problem—optimization of the technological process of benzene production.

Improving Northeast China’s soybean and maize planting structure through subsidy optimization considering climate change and comparative economic benefit

The planting structure of Northeast China (NEC) is greatly responsible for China’s food security and self-sufficiency. Climate change promoted the northward expansion of the suitable planting area for maize in NEC, and its higher comparative economic benefit largely helped it occupy the soybean planting space. Yet, knowledge on how climatic suitability and comparative economic benefit affected the northward expansion of maize planting area is limited. To bridge this gap, this study quantified the climatic suitability of maize and soybean from 1981 to 2020 using the fuzzy mathematical method. Combined with yield, crop distribution and social economic data in 2000, 2010 and 2020, this study further calculated the comparative economic benefit between the two crops. Furthermore, a crop planting decision simulation model was developed to clarify the impact of climatic suitability and comparative economic benefit on the planting area of soybean and maize. Results showed that from 2000 to 2010, the maize planting area increased dramatically. This was due to the continuous northward expansion of the most suitable region (S1) for maize from 47.63°N to 48.43°N before 2010, along with the fact that 65% of the total area was more profitable to plant maize. From 2010 to 2020, the maize planting area partially retreated, mainly due to the shrinking trend of the northern boundary of S1 for maize and the implementation of soybean producer subsidy. The improvement of maize climatic suitability played a fundamental role in the northward expansion of its planting area. On this basis, the comparative economic benefit was critical for planting proportion adjustments. The current soybean producer subsidy largely reduced the profit gap between the two crops, but it was still insufficient in nearly one-third of the total area. This study suggested to increase amount of soybean subsidies in the identified soybean-maize imbalanced regions. Specifically, the average recommended increase amounts ranged from 756 to 2052 CNY/ha depending on the regions. These findings could provide valuable references for understanding the motivation of crop planting decisions and optimizing the corresponding subsidy policies.

Assessing the Susceptibility of the Xiangka Debris Flow Using Analytic Hierarchy Process, Fuzzy Comprehensive Evaluation Method, and Cloud Model

The seasonal Xiangka debris flow, breaking out frequently in Xinghai County, Qinghai Province, poses a serious threat to resident safety, has significant potential economic impacts, and inflicts severe damage on the geological environment, vegetation, and land resources in the area. Therefore, a susceptibility assessment is crucial. Utilizing data from field investigations, meteorology, and remote sensing, this study devised an assessment system using 10 evaluation factors with pronounced regional characteristics as susceptibility indices. Based on data processing using ArcGIS 10.7 and MATLAB R2016B, this study assessed the susceptibility of the Xiangka debris flow using AHP, the fuzzy comprehensive evaluation method, and a cloud model. The analysis results show that, based on AHP, the primary index affecting the occurrence of Xiangka debris flow is mainly source factor (0.447). The secondary indices are mainly the length ratio of the mud sand supply section (0.219), fractional vegetation cover (FVC, 0.208), and watershed area (0.192). Combined with the actual characteristics, it can be seen that the formation conditions of the Xiangka debris flow primarily encompass the following: sources such as slope erosion and accumulation at gully exits, challenging topography and terrain conducive to the accumulation of water and solid materials, and water source aspects like surface runoff from intense rainfall. Based on the fuzzy mathematical method—fuzzy coordinate method—cloud model, it is concluded that the degree of susceptibility is mild-to-moderate. The combination of these methods provides a new idea for the evaluation of debris flow susceptibility. This study can provide a theoretical basis for the layout of treatment engineering and geological disaster prevention in this area and promote the sustainable development of the ecological environment.

Evaluation of Deep Coalbed Methane Potential and Prediction of Favorable Areas within the Yulin Area, Ordos Basin, Based on a Multi-Level Fuzzy Comprehensive Evaluation Method

The research on the deep coalbed methane (CBM) in the Ordos Basin is mostly concentrated on the eastern margin of the basin. The geological resources of the Benxi Formation in the Yulin area, located in the central-eastern part, cover 15,000 × 108 m3, indicating enormous resource potential. However, the characteristics of the reservoir distribution and the favorable areas are not yet clear. This research comprehensively performed data logging, coal rock experiments, and core observations to identify the geological characteristics of the #8 coal seam, using a multi-level fuzzy mathematics method to evaluate the favorable area. The results indicate the following: (1) The thickness of the #8 coal in the Yulin Block ranges from 2.20 m to 11.37 m, with depths of between 2285.72 m and 3282.98 m, and it is mainly underlain by mudstone; the gas content ranges from 9.74 m3/t to 23.38 m3/t, showing a northwest–low and southeast–high trend. The overall area contains low-permeability reservoirs, with a prevalence of primary structural coal. (2) A multi-level evaluation system for deep CBM was established, dividing the Yulin Block into three types of favorable areas. This block features a wide range of Type I favorable areas, concentrated in the central-eastern, northern, and southwestern parts; Type II areas are closely distributed around the edges of Type I areas. The subsequent development process should prioritize the central-eastern part of the study area. The evaluation system established provides a reference for selecting favorable areas for deep CBM and offers theoretical guidance for targeted exploration and development in the Yulin area.

Assessing Changes in Climatic Suitability for Sesame Cultivation in China (1978–2019) Based on Fuzzy Mathematics

Sesame is one of the important oil seed crops grown for the high-quality oil. Its growth, development, and yield are significantly affected by the changing climate conditions. Evaluating the sesame climatic suitability is crucial to optimize sesame cultivation patterns and planting distribution, and to aid strategic decision making for future agricultural adaptation. Based on agricultural climatic suitability theory and the fuzzy mathematics method, in this study, we established the temperature, precipitation, sunshine, and comprehensive suitability model. Then, we assessed the spatial distribution and chronological changes in climatic suitability under two periods, 1978–1998 (earlier 21 years) and 1999–2019 (latter 21 years). The results showed that compared with the meteorological data in the earlier 21 years, the mean temperature during the sesame-growing season in the latter 21 years increased from 24.48 °C to 25.05 °C, and the cumulative precipitation increased from 744.38 mm to 754.81 mm; however, the sunshine hours decreased from 6.05 h to 5.55 h. Temperature, precipitation, sunshine, and comprehensive suitability during the sesame-growing season in the main sesame-producing areas of China all had a downward trend. The distribution of temperature and comprehensive suitability in the north is higher than that in the south, while the precipitation and sunshine suitability had an uneven distribution. The area of high-temperature suitability and high-precipitation suitability increased from 43.45 × 106 ha to 46.34 × 106 ha and from 3.20 × 106 ha to 7.97 × 106 ha, respectively, whereas the area of high-sunshine suitability decreased from 4.04 × 106 ha to 2.09 × 106 ha. The climate change was more beneficial to sesame cultivation in northeast Anhui where the area of high climatic suitability clearly expanded, and in eastern Jiangxi where the area of the general climatic suitability increased. In contrast, it is worth noting that the area of high climatic suitability in northern Henan decreased and the area of low climatic suitability in Hubei increased. Our results have important implications for improving agricultural production to cope with ongoing climate change.

A Case Study: Evaluation of Urban Flood Resilience Based on Fuzzy Mathematics and VIKOR Method in Ulsan Metropolitan City, South Korea

In this study, fuzzy mathematics and VIKOR were employed to develop a flood vulnerability assessment system for Ulsan Metropolitan City, South Korea in 2018. HEC-HMS model was used to simulate the major rivers' runoff in Ulsan Metropolitan City, and HEC-RAS model was used to convert the 1-D runoff simulation results into 2-D results of inundation map, while the simulation results were exhibited through ArcMap. Hazards, sensitivity and adaptivity were selected as the three evaluation indicators for fuzzy comprehensive evaluation, and pressure resilience, state resilience and response resilience were utilized as the indicators for ranking and comparison of the VIKOR method for local governments (administrative districts) of Ulsan Metropolitan City. As the result, Dong-gu district, Ulju-jun County and Nam-gu district showed the best results by both the fuzzy mathematical and the VIKOR method in hazard and pressure, sensitivity and state, adaptivity and response indicator. Fuzzy mathematics and the VIKOR method provide two different ways to study the flood protection capacity of Ulsan Metropolitan City, comparing the historical statistics, VIKOR method's evaluation results match well with the flooding statistics in Ulsan Metropolitan City.

Application of high-dimensional multi-objective differential evolutionary algorithm based on global ordering to heat supply pipe network resistance identification

The distribution of resistance coefficients of heat supply pipe networks is the key data guiding the hydraulic balance adjustment of heat networks. Since the heat supply pipe network is composed of many pipe segments and the resistance coefficient of each pipe segment is different during heat supply operation, the identification of the resistance coefficient of the heat supply pipe network is an optimization problem with multiple objective functions. In this paper, a high-dimensional multi-objective differential evolutionary algorithm based on global sorting is developed as a method to identify the resistance coefficients of the heat network and the multi-objective algorithm is applied to the resistance identification of the heat network, and the computational process of resistance identification is improved. The fuzzy mathematical method is applied to the process of resistance identification, and a set of optimal solution sets are generated through the identification of each pipe segment and the optimal solutions are selected from the optimal solution sets based on the fuzzy degree of subordination to solve the problem of determining the optimal solutions. The problem of determining the optimal solution is solved. The results show that compared with the single-objective algorithm, the high-dimensional multi-objective differential evolutionary algorithm based on global sorting produces a uniform and concentrated optimal solution set, and the optimal solution accuracy is higher.

Effect of heat pump drying temperature on moisture migration characteristics and quality of instant Tremella fuciformis

Low-field nuclear magnetic resonance (LF-NMR) was used to analyze the moisture migration characteristics and water distribution of instant Tremella fuciformis (ITF) during heat pump drying at 35 °C, 45 °C and 55 °C. A fuzzy mathematical evaluation method was then used to investigate the effect of heat pump drying temperatures (35 °C, 45 °C and 55 °C) on the quality of ITF. Based on the screened appropriate temperature of 45 °C, the thin layer heat pump drying curve and drying rate curve of ITF were drawn, then four mathematical models were tested based on the coefficient of determination (R2). The result showed three water components (bound water (T21), immobilized water (T22), and free water (T23)) in ITF before drying. During the drying process, the heat pump drying of ITF was carried out gradually from the outer to the inner. The sensory total score (77.66 ± 6.57), rehydration ratio (4803.00 ± 90.00%), and viscosity (45.01 ± 3.61 Pa s) of ITF in heat pump drying at 45 °C were the best. The optimal drying temperature of 45 °C was obtained by the fuzzy comprehensive evaluation with the highest comprehensive score of 77.85%. With the prolongation of drying time, the water content of ITF showed a gradual decreasing trend, and the water content was controlled to below 8.51% after 6 h. The drying curve shows that the drying phase of the ITF is divided into three phases, including preheat, constant speed and deceleration. The drying speed first increases, remains constant in the middle and then decreases. Among the four models tested, the cubic regression equation aligned with the change rule of the ITF drying curve (R2 = 0.99397). By studying the effect of drying temperature on the moisture migration characteristics and the quality of ITF, we aim to provide more data support for the production of T. fuciformis.

Method of operating assessment of the state of network elements to ensure the quality of services in corporate high­speed multiservice communication networks

The article proposes intelligent methods and algorithms for operational assessment of the state of network elements to ensure indicators of the quality of communication services in corporate multi-service communication networks that function in a mode close to real time. A feature of corporate multi-service networks is the high dynamics of changes in their state. And the task of the automated network management system is to ensure the given quality of communication services. Thus, the relevance of this study is determined by the need to implement network management processes in a mode close to real time, with a given quality. The basis of the method of operational assessment of the state of network elements is the concept of using intelligent agents. In the proposed approach, intelligent agents are created as hierarchical fuzzy situational networks, in which management decisions, in contrast to known methods based on the application of reference situations, are produced on the basis of solving a hierarchical system of optimization tasks based on fuzzy mathematical programming methods. The main paradigm of their functioning is «situation – action». This makes it possible to significantly reduce the dimension of the task to be solved and obtain Pareto-optimal solutions for managing the quality of communication services. The intelligent agent of management solutions can be implemented automatically, provided that the network administrator delegates such capabilities to it. The method of estimating traffic parameters is based on the concept of conditional nonlinear Pareto-optimal filtering. Its essence is to apply a two-stage procedure; at the first stage, a forecast of the values of parameter estimates is made, but in the second, with the receipt of the following observations, their values are adjusted. The average relative error of traffic parameter estimation does not exceed 10%, which is sufficiently operational for managing the quality of communication services.

Comprehensive Evaluation of Coal Mine Production Safety Based on Fuzzy Comprehensive Evaluation

In view of the potential safety hazards existing in the production and operation process of coal mining enterprises, through expert consultation and comprehensive investigation, sort out the relevant risk factors, establish the corresponding coal mine production risk evaluation index system, conduct fuzzy comprehensive evaluation by combining AHP and fuzzy mathematical evaluation method, and calculate the weight of each index and the risk level of coal mine production, Finally, through a case study of a coal mine in Inner Mongolia Autonomous Region, the feasibility of the risk evaluation method is verified, which provides a theoretical basis for coal mine production enterprises to formulate risk management schemes and a reference for risk management of coal mine production industry.

Comprehensive evaluation of thermally conductive functional layer on snow-melting performance for electric heating bridge system

The most commonly used chemical salt agents for melting ice and snow can lead to the corrosion of the steel structure of the bridge deck, as well as potential pollution of nearby rivers and soil through infiltration and surface runoff. The heating bridge system with electric cable is a promising environmentally friendly technology for snow removal. However, the unique suspension and multi-layer characteristics of the bridge pavement make it challenging to efficiently transfer the heat generated by the electric heating bridge system to the pavement surface. To enhance snow-melting efficiency, a novel directional heat transfer electric heating bridge system with a thermally conductive functional layer (EHBS-TCFL) has been introduced. Initially, a series of tests, including thermal conductivity tests, compressive tests, and bending tests, were performed on TCFL with different mix ratios. Then the TCFL with the most favorable mix ratios was determined based on the fuzzy mathematics method. Subsequently, the heating and snow-melting performance of EHBS-TCFL was evaluated. The results indicated that the thermally conductive functional layer, which includes reduced iron powder with a water-cement ratio of 0.53 and an iron powder-cement ratio of 2, represents the optimal solution for achieving exceptional thermal conductivity, flexural strength, and compressive strength. Furthermore, the presence of TCFL positively impacts the enhancement and uniformity of surface temperatures, leading to a 12.7% increase in total energy utilization efficiency. This study offers significant potential for the application of snow-melting on bridge decks in cold regions.

Hydrocarbon gas huff-n-puff optimization of multiple horizontal wells with complex fracture networks in the M unconventional reservoir

The oil production of the multi-fractured horizontal wells (MFHWs) declines quickly in unconventional oil reservoirs due to the fast depletion of natural energy. Gas injection has been acknowledged as an effective method to improve oil recovery factor from unconventional oil reservoirs. Hydrocarbon gas huff-n-puff becomes preferable when the CO2 source is limited. However, the impact of complex fracture networks and well interference on the EOR performance of multiple MFHWs is still unclear. The optimal gas huff-n-puff parameters are significant for enhancing oil recovery. This work aims to optimize the hydrocarbon gas injection and production parameters for multiple MFHWs with complex fracture networks in unconventional oil reservoirs. Firstly, the numerical model based on unstructured grids is developed to characterize the complex fracture networks and capture the dynamic fracture features. Secondly, the PVT phase behavior simulation was carried out to provide the fluid model for numerical simulation. Thirdly, the optimal parameters for hydrocarbon gas huff-n-puff were obtained. Finally, the dominant factors of hydrocarbon gas huff-n-puff under complex fracture networks are obtained by fuzzy mathematical method. Results reveal that the current pressure of hydrocarbon gas injection can achieve miscible displacement. The optimal injection and production parameters are obtained by single-factor analysis to analyze the effect of individual parameter. Gas injection time is the dominant factor of hydrocarbon gas huff-n-puff in unconventional oil reservoirs with complex fracture networks. This work can offer engineers guidance for hydrocarbon gas huff-n-puff of multiple MFHWs considering the complex fracture networks.

Особливості розрахунку очікуваної вартості дослідно-конструкторських робіт зі створення космічних апаратів

The aim of this work is to identify the features of expected cost estimation for R&D’s on spacecraft development. The study is based on a methodological approach to expected cost estimation for R&D’s on spacecraft development. The cost estimation model is based on a method of componentwise analogy for relatively simple spacecraft components, moving along the edges of a weighted oriented tree graph that models the spacecraft technical structure, and fuzzy mathematics methods. The methodological approach will allow one to obtain required R&D expected cost indices early in the spacecraft development when the standardized cost estimation method and parametric methods are difficult to use because of the insufficiency of bug-free design and manufacture documentation and statistical data on labor intensiveness and materials consumption. The design novelty, R&D complexity, and work automation coefficients are determined by converting the index value from a fuzzy number in a fuzzy interval into a crisp number, thus allowing one to reduce the effect of subjective factors. Calculating the engineering-and-economical indices of a spacecraft by all R&D participants using the same methodological approach increases the accuracy and shortens the time of the computational process. Conducting the calculations in a systematic way will fill the statistical base of the space sector with labor intensiveness and materials consumption data needed for estimating the cost of new spacecraft and components thereof using a unified concept package – a glossary. The paper presents the operation sequence of estimating the cost of R&D on spacecraft development and describes the required input data and the output data format.

Phytoplankton Community Structure, Diversity, and Functional Groups in Urban River Under Different Black and Odorous Levels

Phytoplankton community characteristics, diversity, and functional group analysis can respond to the environmental quality status of water bodies. To investigate the influence of urban river black odors on the phytoplankton community, from November 2020 to March 2021, 16 urban rivers in the Sichuan Basin were surveyed for water quality with 38 sampling points, and the degree of urban river black odor was evaluated based on the improved fuzzy mathematical model method and the k-mean principal color extraction method. The rivers were classified into four types:non-black and non-odorous, black and non-odorous, black and odorous, and black and odorous. The results showed that, with black and odorous water, the phytoplankton abundance increased from 1.329×105 cells·L-1 to 6.627×105 cells·L-1, and the dominant phytoplankton phylum decreased from Cyanophyta-Chlorophyta-Bacillariophyta to Cyanophyta. The phytoplankton biomass increased from 64.056 μg·L-1 to 120.465 μg·L-1, and the dominant phytoplankton phylum changed from Chlorophyta-Bacillariophyta type, adapted to a nutrient environment, to Pyrrophyta-Bacillariophyta-Cryptophyta type, adapted to an organic matter environment. The Shannon-Weaver diversity index decreased from 2.45 to 1.98, and Simpson's index decreased from 0.84 to 0.73. Twenty nine functional groups of phytoplankton were observed in the study area, and the growth strategy was reduced from S, R, C, CR, and CS to R with black and odorous water. In summary, phytoplankton indicators can better reflect the state of river black odor, and phytoplankton monitoring is a promising tool for urban river black odor management.

Oxygen comfort evaluation method based on symptom index for short-term internal migrants to Tibet

In Tibet, the hypobaric-hypoxic environment found at high altitudes leads to dysfunction in short-term internal migrants and has noticeable effects on physiology, psychological health, and comfort level. Therefore, it is essential to accurately determine the degree of hypoxia and improve the hypoxic environment of plateaus. Despite advances in the medical diagnosis and treatment of pathological hypoxic injuries, there are some limitations in the oxygenic evaluation of internal migrants with mild hypoxia. An oxygen comfort evaluation method (OCEM) based on typical anoxic symptomatology and physiological indices is proposed in this study. Experiments with different oxygen concentrations were conducted to measure anoxic symptomatology and physiological indices. Using item and exploratory factor analyses, 19 symptom indices were screened to predict oxygen sensation in humans. Finally, the OCEM was established using an artificial neural network and fuzzy mathematics method and its accuracy was verified through a field survey. The results showed that the artificial neural network model using symptomatologic indices could predict human oxygen sensation, with an area under the receiver operating characteristic curve of 0.630–0.913 and prediction accuracy of 93 %. Oxygen comfort can be predicted from the oxygen sensation and typical physiological indices using the fuzzy mathematics method; the weighted kappa coefficient was 0.825, indicating a strong correlation between the predicted and actual values. The proposed OCEM can help determine the oxygen comfort conditions of high-altitude internal migrants and provide a basis for indoor oxygen environment regulation in high-altitude buildings.

Analysis of the Expression of Buddhist Monks’ Literary Activities in the Early Sui and Tang Periods Based on Fuzzy Mathematical Models

Abstract Buddhist culture was widely spread in Chang’an during the Sui and Tang dynasties, and as the center of literary development in the country at that time, literary works in Chang’an were influenced by Buddhist literary activities from form to content. This paper first analyzes the current situation of Buddhist literary activities in the Sui and Tang dynasties, applies fuzzy mathematical theory to the analysis of literary activities based on the research of domestic and foreign experts and scholars on the manifestation of literary activities, and establishes an analysis model of literary activities based on fuzzy mathematical methods. Secondly, Buddhist thought is fitted through the closeness of a fuzzy mathematical model. The weights among the influencing factors of Buddhist literary expressions were determined through characteristic factors and affiliation degrees. The experimental results show that the deviation rate of the expression form analysis of Buddhist monks’ literary activities based on the fuzzy mathematical model in the early Sui and Tang dynasties ranges from 5% to 10%, but the deviation rate of the final overall estimation accuracy does not exceed 5%, which verifies that the model can be applied to the expression form analysis of literary activities. The fuzzy mathematical model proposed in this paper is more accurate than the traditional method of literary activity analysis and yields the highest degree of closeness, which is a guide to the study of traditional cultural transmission and integration and provides a new way of thinking for the transmission of traditional culture.

Retraction: Wei, Wei and Lu, Liu. “The influence of X fuzzy mathematics method in basketball tactics scoring” Applied Mathematics and Nonlinear Sciences, vol.7, no.1, 2022, pp.677-684

Retraction: Wei, Wei and Lu, Liu. “The influence of X fuzzy mathematics method in basketball tactics scoring” Applied Mathematics and Nonlinear Sciences, vol.7, no.1, 2022, pp.677-684

Solving multi-objective linear fractional decentralized bi-level decision-making problems through compensatory intuitionistic fuzzy mathematical method

This study has focused on developing a new method for solving the multi-objective linear fractional decentralized bi-level decision-making (MOLF-DBLDM) problem in an intuitionistic fuzzy decision environment. The main motivation behind this study is to determine a solution approach algorithm that is effective and simple to apply while taking actual decision-making circumstances into account. Real-world decision-making situations involve a bi-level of several decision-makers who use various decision-making processes such as agree, not certain, and disagree. By considering such real-world conditions here, all uncertain coefficients of objectives, constraint functions, and resources are portrayed as trapezoidal intuitionistic fuzzy numbers, and their crisp form is obtained through the (α,β)-cut (confidence level) concept. In the suggested method, we have transformed the crisp (α,β)-MOLF-DBLDM problem into a single objective linear decentralized bi-level decision-making (SOL-DBLDM) model using a modified linearized approach. Additionally, the upper level specified a tolerance region for its decision variables to regulate the lower levels in order to prevent decision lock. Then, the SOL-DBLDM problem is expressed as a single-level model using a new scalar function of membership and non-membership degree for each objective function at all decision-makers and upper level decision control variables. The key advantage of this method over others is that it produces an alternate, preferable compromise solution to the problem of imprecise hierarchical-level optimization. Finally, comparisons to the current methodology and appropriate numerical examples are used to demonstrate the superiority and effectiveness of the suggested method.

Analysis and Improvement of Oversize Goaf Backfill Engineering Based on Fuzzy Theory

For the mine of large goaf, there are many factors that affect the filling quality. In order to improve the filling quality, it is necessary to identify the factors that have a significant impact. In this paper, the fuzzy mathematical method was used to analyze the five main factors (PC32.5cement sand ratio, slurry concentration, number of slurry lowering, dehydration and drainage, and tailing particle size grading) affecting the filling quality. The priority of each influence factor was calculated, and the priority set was established. It is found that the slurry launching point and particle size grading of the tailings have an obvious effect on filling quality. After increasing the slurry launching point and optimizing the particle size grading, the strength and uniformity of the filling body are improved.