Abstract:Recently, a huge amount of online consumer reviews (OCRs) is being generated through social media, web contents, and microblogs. This scale of big data cannot be handled by traditional methods. Sentiment analysis (SA) or opinion mining is emerging as a powerful and efficient tool in big data analytics and improving decision making. This research paper introduces a novel method that integrates neutrosophic set (NS) theory into the SA technique and multi-attribute decision making (MADM) to rank the different pro… Show more
“…The 3D FFT performance of the GPU group used by Parray was tested on Tianhe 1A and compared with Intel MKL 10.3.1.048 [21]. Figure 4 is the 3D FFT comparison of different scales of the same hard disk (figure PKUFFT is the 3D FFT model of the GPU group used by Tianhe-1 A Parray).…”
In order to adapt to the constantly updated heterogeneous hardware and super-large-scale parallel computing environment and solve the problems of low programming level and difficult development, modification, and debugging of commonly used solutions, the author proposes a method for application communication optimization and computer big data management based on heterogeneous clusters. A new language mechanism is introduced to describe the multidimensional rule structure, arrangement, and communication mode of data and threads; and a software migration and optimization method between different types of heterogeneous systems based on the new language mechanism is proposed. And take direct method turbulence simulation as an example. Experimental results show that based on the Parray mechanism, it took only one week to complete the rapid migration of turbulence simulation applications on the Tianhe 1A system, and it was successfully run on a scale of 8192 cubic meters. Conclusion. The method realizes communication optimization and fast porting in different heterogeneous systems.
“…The 3D FFT performance of the GPU group used by Parray was tested on Tianhe 1A and compared with Intel MKL 10.3.1.048 [21]. Figure 4 is the 3D FFT comparison of different scales of the same hard disk (figure PKUFFT is the 3D FFT model of the GPU group used by Tianhe-1 A Parray).…”
In order to adapt to the constantly updated heterogeneous hardware and super-large-scale parallel computing environment and solve the problems of low programming level and difficult development, modification, and debugging of commonly used solutions, the author proposes a method for application communication optimization and computer big data management based on heterogeneous clusters. A new language mechanism is introduced to describe the multidimensional rule structure, arrangement, and communication mode of data and threads; and a software migration and optimization method between different types of heterogeneous systems based on the new language mechanism is proposed. And take direct method turbulence simulation as an example. Experimental results show that based on the Parray mechanism, it took only one week to complete the rapid migration of turbulence simulation applications on the Tianhe 1A system, and it was successfully run on a scale of 8192 cubic meters. Conclusion. The method realizes communication optimization and fast porting in different heterogeneous systems.
“…The questionnaire is designed according to the constructed firstand second-level index system, and four options of "very satisfied (A), satisfied (B), relatively satisfied (C), and dissatisfied (D)" are set for each indicator to facilitate users' selection. The "A" level corresponds to 100 points, the "B" level corresponds to 85 points, the "C" level corresponds to 75 points, and the "D" level corresponds to 60 points [24,25].…”
Section: Evaluation Of System Application Usementioning
In order to solve the problem that the traditional operation and maintenance system of photovoltaic operation and power station is mainly based on statistical analysis and multisite and multilevel deployment mode, which wastes software and hardware resources, is not easy to expand and has extremely low efficiency, which cannot meet the urgent needs of users to reduce costs and increase efficiency. This research proposes a methodology for integrating big data, cloud computing, and photovoltaic operation and maintenance. This method constructs the business model, data model, application model, and technical model of the photovoltaic power station operation and maintenance cloud platform. The results obtained are as follows: the system provides diagnostic services for the application system of a 30 MWp photovoltaic power station in a certain place, and a total of 87 defects are found, the defect elimination rate is 88.51%, and the monthly power generation of the power station is increased by 122,529 kWh; the use effect of the system in this research after it goes online. The evaluation is 93.04 points, ranging from very satisfactory (A) to satisfactory (B) and biased towards A, indicating that the use effect is good. It is proved that the successful research and promotion of the system in this research will be of great significance to improve the intelligent operation and maintenance level of photovoltaic power plants and improve the operation and maintenance efficiency of photovoltaic power plants.
“…Platform. Starting from the characteristics of forest ecological data, a forest ecological big data platform based on Hadoop is proposed, which can be used for data management of ecological stations distributed all over the country [11]. The platform deeply integrates big data, Internet of Things, artificial intelligence, and other technologies to provide users with rapid retrieval, processing, and visual analysis of forest ecological data [12].…”
Section: Overall Architecture Of Forest Ecological Big Datamentioning
In order to solve the problems of low data storage efficiency and poor retrieval performance in forest ecological station, a method of a forest ecological station data management platform based on Internet of Things and big data sensor is proposed. The framework method designs the prepartition algorithm to ensure the uniform distribution of data in the cluster. According to the characteristics of ecological data, the RowKey is scientifically designed to realize the rapid retrieval of ecological data. The Elasticsearch index fragment placement strategy based on index data and server performance evaluation is designed, and the packaging and merging strategy based on data site and time correlation is proposed to improve the storage efficiency. The results are as follows: when the scale of structured data is 108, the retrieval time of the system is 1.045 s, which is 3.99 times faster than that of the original HBase. When the scale of unstructured data is 107, the packaging small image strategy based on data site and time correlation is 1.15 times higher than that of the sequence file and 1.79 times higher than that of the original HBase. In the case of 104 concurrent users, the number of queries per second after optimization is 1.88 times higher than the original, the throughput per second is 1.74 times higher than that before optimization, and the system response time is 69.5% lower than that before optimization. The results show that the proposed scheme has significantly improved the performance in the aspects of cluster load balancing and massive structured and unstructured data retrieval efficiency and system throughput, and provide the necessary theoretical basis and technical implementation for the storage and management of forest ecological data.
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