Research on application of ReliefF and improved RVM in water quality grade evaluation

ReliefF algorithm was used to analyze the weight of each water quality evaluation factor, and then based on the Relevance Vector Machine (RVM), Particle Swarm Optimization (PSO) was used to optimize the kernel width factor and hyperparameters of RVM to build a water quality evaluation model, and the experimental results of RVM, PSO-RVM, ReliefF-RVM and PSO-ReliefF-RVM were compared. The results show that ReliefF algorithm, combined with threshold value, selects 5 evaluation factors with significant weight from 8 evaluation factors, which reduces the amount of data used in the model, CSI index is used to calculate the separability of each evaluation factor combination. The results show that the overall separability of the combination is best when the evaluation factor with significant weight is reserved. When different water quality evaluation factors were included, the evaluation accuracy of PSO-ReliefF-RVM model reached 95.74%, 14.23% higher than that of RVM model, which verified the effectiveness of PSO algorithm and ReliefF algorithm, and had a higher guiding significance for the study of water quality grade evaluation. It has good practical application value.

Water Quality Evaluation of Wenyu River in Beijing by Matter Element Model

River water quality is an important indicator for identifying river changes and analyzing river health, and has an important impact on the ecological environment of the river basin. In this paper, the matter-element analysis method based on the coupling weight method is used to evaluate the water environment of the water quality measured data of Wenyu River in 2019, which provides a reference for water quality management and protection. Through the establishment of the object element to be evaluated, the classical domain, the section domain, the normalization of the evaluation standard, and the measured data, three representative indicators such as DO, NH3-N, and CODcr are selected as the object element to be evaluated. The standard value corresponding to the water quality standards of Grade I to V is the classic domain. The weight of river indicators is determined by the coupling of the ordinary objective weighting method and the multiple super-scale weighting method. After the weight is determined, the correlation degree is calculated and the matter-element analysis model for water quality evaluation is established. The results showed that the water quality of the Wenyu River in May 2019 was still mainly Grade V water, which was in line with the actual water quality situation. It shows that the method meets the feasibility and practicability in water quality evaluation and is relatively reliable.

High-Performance Computational Early Warning Analysis of Agricultural Economy Relying on Binary Fuzzy Cluster Analysis Algorithm

In this paper, a binary fuzzy cluster analysis algorithm is used for an in-depth study and analysis of high-performance computational early warning in the agricultural economy. The definition of interval type-two fuzzy set and its operation are summarized. Considering the uncertain information that will be encountered in the evaluation process, this paper constructs the evaluation model of rural informatization construction performance based on interval type-two fuzzy numbers, which improves the accuracy of the evaluation results. The fuzzy clustering centres are modified according to the nature of the fuzzy clustering centre matrix, and the optimal fuzzy clustering centres and optimal fuzzy clustering division matrix with consistent order are solved. Using the level eigenvalues to find out in the abundant water period, there are 4 monitoring sections of water quality evaluation results for still clean and 5 monitoring sections of water quality evaluation results for slight pollution. In the flat-water period, there are 2 monitoring sections of the water quality evaluation results that are still clean and 7 monitoring sections of the water quality evaluation results are slightly polluted. In the dry water period, the water quality evaluation results of the 9 monitoring sections are slightly polluted. The results and the use of integrated pollutant index evaluation method results are consistent, indicating that the use of fuzzy clustering model for water quality evaluation is practical and effective. Its functional structure includes management business, innovation business, service business, production business, and operation business functions, in addition to the design of the collection and storage scheme based on Hadoop data warehouse, to achieve accurate matching of information of science and technology agricultural services in the whole agricultural industry chain. Finally, the implementation and maintenance of the cloud-based science and technology agricultural service information system are deployed, and the operational effects of its information system-related functions are demonstrated using prototype design. This paper constructs a comprehensive information system for science and technology agricultural services based on cloud technology that integrates management, innovation, service, production, and operation, which meets not only the needs of traditional science and technology agricultural service information systems, such as expert consultation and training demonstration, but also other needs spawned by the development of agricultural modernization.

Characteristics of the Phytoplankton Community Structure and Water Quality Evaluation in Autumn in the Huaihe River (China)

As an important indicator of phytoplankton in water quality evaluation, the phytoplankton community structure is very sensitive to changes in water quality, and analyzing their community composition and function is of great significance for the ecological management and maintenance of watershed environments. To understand the environment and ecological status as well as reconstruct or restore a healthy aquatic ecosystem in the Huaihe River Basin in China, a comprehensive phytoplankton survey was conducted in the main stream and main tributaries of the Huaihe River in 2019. A total of 266 species or genera of phytoplankton were identified, mainly belonging to Bacillariophyta and Chlorophyta. The number of phytoplankton species upstream and downstream was higher than that in the middle. The results of phytoplankton biomass showed significant spatial differences in different river reaches (p < 0.05). The identified phytoplankton functional groups (FGs) were divided into 27 groups, including 16 representative functional groups (RFGs), followed by A, B, F, G, H1, J, K, LM, LO, M, MP, P, T, TB, WO and X2. The mean values of the Shannon–Wiener index and Margalef index were 2.47 and 2.50, respectively, showing that most of the water in the Huaihe River Basin was in a state of moderate nutritional status. The results of this study provided a reference for studying the composition and distribution of phytoplankton communities, nutrient status, and pollution levels in the Huaihe River Basin, as well as in other similar watersheds.

Water Quality Evaluation of Wenyu River Based on Single Factor Evaluation and Comprehensive Pollution Index Method

Wenyu River is the “mother river” in Beijing. In recent years, the research on the water quality of the Wenyu River has increased gradually. In this paper, the monitoring data at Shahe Reservoir, Lu Tuan Gate, Xin Bao Gate, and Ma Fang sections for each month in 2019 were adopted. The single-factor evaluation method and the comprehensive pollution index method were selected to analyze the current situation of the water quality of Wenyu River in the Chang Ping section and its temporal and spatial variation trend. The single factor evaluation method showed that the dissolved oxygen exceeded the standard seriously in all other months of the year except that the situation was better in May, June, and July. The ammonia nitrogen content reached the highest level in January, followed by a month-by-month decreasing trend. After June, each section basically met the requirements of Class v water quality. The comprehensive pollution index method shows that the water quality of Shahe reservoir varies greatly throughout the year, and it is in grade v for 6 months. The evaluation results of both methods show that the water quality of all sections of Wenyu River in 2019 was mostly in category v.