Comprehensive Evaluation of Land Reclamation Schemes in Mining Area based on Linguistic Intuitionistic Fuzzy Group Decision Making

Mine geological environment protection and land reclamation schemes are the core requirements for mining right application, which play an important role in regulating mining activities and supervising mining enterprises to fulfill their obligations of mine reclamation. In order to give full play to the guidance function of the schemes, provide reference for the compilation and review of the schemes, this paper attempts to make comprehensive evaluation of land reclamation schemes in mining area with multi-attribute group decision making method. First, linguistic intuitionistic fuzzy numbers are utilized to describe the evaluation information. Considering the authority and preference attitude of experts, the determination methods of expert weights in four cases are established. Then max-min deviation method is used to determine the attribute weights. Thereafter, a method for Linguistic intuitionistic fuzzy group decision making problem is proposed. Finally, the practicability of this method is verified by land reclamation schemes of four mining areas in Sichuan Province and comparative analysis is made. The research results show that the evaluation process of this method is simple and effective, so it can be reasonably applied to compile and review of land reclamation schemes.

Distribution Linguistic Fuzzy Group Decision Making Based on Consistency and Consensus Analysis

The development of distribution linguistic provides a new research idea for linguistic information group decision-making (GDM) problems, which is more flexible and convenient for experts to express their opinions. However, in the process of using distribution linguistic fuzzy preference relations (DLFPRs) to solve linguistic information GDM problems, there are few studies that pay attention to both internal consistency adjustment and external consensus of experts. Therefore, this study proposes a fresh decision support model based on consistency adjustment algorithm and consensus adjustment algorithm to solve GDM problems with distribution linguistic data. Firstly, we review the concept of DLFPRs to describe the fuzzy linguistic evaluation information, and then we present the multiplicative consistency of DLFPRs and a new consistency measurement method based on the distance, and investigate the consistency adjustment algorithm to ameliorate the consistency level of DLFPRs. Subsequently, the consensus degree measurement is carried out, and a new consensus degree calculation method is put forward. At the same time, the consensus degree adjustment is taken the expert cost into account to make it reach the predetermined level. Finally, a distribution linguistic fuzzy group decision making (DLFGDM) method is designed to integrate the evaluation linguistic elements and obtain the final evaluation information. A case of the evaluation of China’s state-owned enterprise equity incentive model is provided, and the validity and superiority of the proposed method are performed by comparative analysis.

Complex Fuzzy Groups Based on Rosenfeld’s Approach

Complex fuzzy sets (CFS) generalize traditional fuzzy sets (FS) since the membership functions of CFS reduces to the membership functions of FS. FS values are always at [0, 1], unlike CFS which has values in the unit disk of C. This paper merges notion and concept in group theory and presents the notion of a complex fuzzy subgroup of a group. This proposed idea represents a more general and better optional mathematical tool as one of the approaches in the fuzzy group. However, this research defines the notion of complex fuzzy subgroupiod, complex fuzzy normal subgroup, and complex fuzzy left(right) ideal. Therefore, the lattice, homomorphic preimage, and image of complex fuzzy subgroupiod and ideal are introduced and studied its properties. Finally, complex fuzzy subgroups and their properties are presented and investigated

Intelligent rail lubrication system based on fuzzy group analysis

The security of a train becomes a more critical issue as the train’s speed and the complexity of the railway conditions increases. It is especially true when the train runs on a curved radius rail when the lateral force between the train and the rail is less stable. The rail’s side grinding is a significant problem that affects the train’s safety, especially when the train passes through small radial sections in mountainous areas. The intelligent rail lubrication system is critical to enhancing rails’ safety and efficiency and reducing grease pollution along rail lines. This system is modeled with a force analysis of train curve motion and numerical simulation of wear power. The lubrication system is constructed with hardware and software. Based on fuzzy group analysis, this system and the adaptive Proportional Integration Differential (PID) controller is presented to improve the lubricative effects. The system test results show that the quality of lubrication control using this system is efficacious; the control convergence is more reliable than the conventional PID controller.

Una Implementación para el Agrupamiento Difuso en SQL

Los sistemas de gestión de bases de datos (SGBD) relacionales tienen una gran utilidad en el almacenamiento eficiente de grandes volúmenes de datos. En este sentido, se han propuesto algunas extensiones de los SGBD basadas en la lógica difusa, para mejorar la expresividad de los lenguajes de consulta, entre ellos, el lenguaje SQLf (extensión de SQL que soporta condiciones difusas). Por otra parte, el Group-By es un operador de base de datos ampliamente utilizado en el análisis de datos y en los sistemas de apoyo a la toma de decisiones. En muchos casos, parece útil agrupar los valores según su similitud con un determinado concepto en lugar de establecer la agrupación sobre la base de valores iguales. En este contexto, se ha propuesto una nueva estructura de SQLf denominada Fuzzy Group By (FGB), para apoyar una agrupación basada en particiones difusas. En este trabajo, se incorporó la agrupación difusa en PostgreSQLf, que es una extensión del SGBD PostgreSQL, para el manejo de consultas difusas utilizando el lenguaje SQLf con una arquitectura fuertemente acoplada (directamente en el SGBD). Se pronone un algoritmo basado en un hash para evaluar el operador FGB y también se evalúa empíricamente el rendimiento de PostgreSQLf sobre el Benchmark™ TPC-H.