Subjects: Geosciences >> Geography submitted time 2024-03-01 Cooperative journals: 《干旱区研究》
Abstract： To objectively reflect the surface water quality status, a combination of the Analytic Hierarchy Process Entropy Weight Method and the weighted average comprehensive evaluation principle were used to improve the fuzzy comprehensive evaluation method. The method was compared with the single factor evaluation, Nemero index, and traditional undefined extensive evaluation methods to evaluate the surface water environmental quality in the Chengde area in 2021. The results showed a significant spatiotemporal difference in the surface water quality. Except for some sections with poor water quality from July to September, the water quality in other sections was in Classes I–III; The main factors affecting surface water quality in the Chengde area were CODMn and TP; The single factor evaluation and the Nemero index methods could not reflect the overall water quality. Compared to the traditional fuzzy comprehensive evaluation method, the improved fuzzy comprehensive evaluation method considers the interaction between various pollution factors and weakened the impact of individual water quality indicators on the evaluation results. It can also rank the category of water quality, making it more suitable for evaluating the environmental quality of surface water in the Chengde area.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-03 Cooperative journals: 《计算机应用研究》
Abstract： Nowadays, many geo-distributed nearby edges have been deployed for providing high quality services to end users, which continuously produce large volume of user data. In order to minimize the average latency for a series of geo-distributed data analytical jobs, this paper first introduced online randomized algorithm ranTA. ranTA actually showed the preference on the task assignment under the consideration of both computing capacity of edges and the network bandwidth. Furthermore, in order to avoid overloading those edges with low computing capacities, this paper proposed data redistribution mechanism ranTA-data based on ranTA by redistributing some data to the central data center along with the tasks. The result of ranTA-data could be proved concentrated on its optimum with high probability. Extensive simulations show that ranTA-data gains nearly 30% improvement compared with current scheduling algorithms.
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