Anti-Interference Technology of Surface Acoustic Wave Sensor Based on K-Means Clustering Algorithm

Fan, Yanping; Liu, Yajun; Qi, Hongli; Liu, Feng; Ji, Xiaojun

doi:10.1109/jsen.2021.3052957

Cited by 21 publications

(8 citation statements)

References 20 publications

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“…Fan et al vividly describe economic growth as two processes: one is called mushroom effect, which refers to the growth, decline, and significant differences caused by the continuous flow of factors from low productivity industries to high productivity industries. The other is called yeast process, which means that all industries show a common development trend affected by the same macroeconomic fundamentals [ 6 ]. Xia et al studied 39 countries as samples, but did not find that the change of manufacturing structure can promote productivity growth [ 7 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Selection and Optimization of Regional Economic Industrial Structure Based on Fuzzy k-Means Clustering Algorithm

Yuan¹,

Gao

2022

Computational Intelligence and Neuroscience

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Learning about the regional business model is essential for the sustainable development of the regional economy. From the perspective of urban renewable energy, city A is the product of energy development. This paper analyzes the current situation and existing problems of the industrial model of city A through fuzzy k-means clustering algorithm. The results show that although the optimization of industrial structure in city A has achieved some results, the more intuitive problems mainly include low labor productivity of the primary industry, strong resource dependence, insufficient extension of industrial chain, and slow development of technology intensive industries. This paper uses fuzzy k-means clustering algorithm to select the leading industries from the perspective of the current situation of leading industries, urban development pattern, and regional policies in city A. The results show that, as a renewable resource-based city, the leading industries suitable for the current development of city A include manufacturing, power, alkali gas and water production and supply, transportation, warehousing and postal industry, leasing, and business services. The results of fuzzy k-means clustering algorithm are quite excellent, and the accuracy rate is 93.3%. This paper uses the grey dynamic linear programming model to predict the future development of the Urban A business model and combines the selection of key functions to obtain the best business model: deep and efficient technical equipment as a good goal, achieved through regional logistics, transportation, new services, etc., to enhance the output value of the tertiary industry in city A and optimize the internal structure of the secondary industry in city A.

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Section: Literature Reviewmentioning

confidence: 99%

Selection and Optimization of Regional Economic Industrial Structure Based on Fuzzy k-Means Clustering Algorithm

Yuan¹,

Gao

2022

Computational Intelligence and Neuroscience

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“…With the rapid development of network technology and cloud computing in recent years, the network has become an indispensable part of production and life, and the dissemination of information has become more and more rapid with the rise of the network [1]. People have more convenient and complete ways to obtain information [2].…”

Section: Introductionmentioning

confidence: 99%

Application of $K$ -Means Clustering Algorithm in Energy Data Analysis

Zhou

2022

Wireless Communications and Mobile Computing

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In order to solve the problem of how to explore potential information in massive data and make effective use of it, this paper mainly studies news text clustering and proposes a news clustering algorithm based on improved K -Means. Then, the MapReduce programming model is used to parallelize the TIM- K -Means algorithm, so that it can run on the Hadoop platform. The accuracy and error are used as measurement indicators, and the collected datasets are used for experiments to verify the correctness and effectiveness of the TI value and TIM- K -Means algorithm. In addition, the Alibaba cloud server is used to build the Hadoop cluster, and the feasibility of parallelization transformation of TIM- K -Means algorithm is verified by accelerated comparison. The results show that the parallelized TIM- K -Means has a good acceleration ratio, can save about 30% of the time under the same conditions, and can meet the actual needs of processing massive data in the context of big data. In multidocument automatic summarization, news clustering algorithm can gather the news with the same topic and provide cleaner and accurate data for visual automatic summarization, which is of great significance in the fields of public opinion supervision, hot topic discovery, emergency real-time tracking, and so on.

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“…The improvement in the activity of the alloyed Pd with Cu can be ascribed to the modulated d-band center, which weakens the bonding of intermediate species such as CO molecules to the surface of the alloy. 41 However, the catalysts with other composition (PdCu 1:9 MNs and PdCu 9:1 MNs) exhibited a smaller current density due to the lack of Pd atoms serving as active sites (i.e., lower ECSAs) (SI Figure S9b). 20 To study the stability the as-prepared PdCu 1:1 MNs, amperometric i-t tests were carried out.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

Tailored Design of Mesoporous PdCu Nanospheres with Different Compositions Using Polymeric Micelles

Iqbal

Kim

et al. 2019

ACS Appl. Mater. Interfaces

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Mesoporous metals have attracted a lot of interest due to their wide range of applications, particularly in catalysis. We previously reported the preparation of mesoporous Pd using block copolymer micelle templates (Chem. Sci. 2019, 10, 4054). Here we extend this synthetic concept to generate alloyed spherical palladium−copper (PdCu) nanoparticles with an open porous network and uniform morphology. This one-pot synthesis is initiated by water-induced micellization of the block copolymer, followed by the chemical reduction, nucleation, and growth of mesoporous spherical alloy nanoparticles. Porosity enables accessibility to numerous active sites throughout the interior and exterior surfaces of the nanoparticles. Mesoporous nanoparticles composed of Pd and Cu alloy exhibit enhanced electrocatalytic activity and stability in the ethanol oxidation reaction (EOR) and the oxygen reduction reaction (ORR).

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Anti-Interference Technology of Surface Acoustic Wave Sensor Based on K-Means Clustering Algorithm

Cited by 21 publications

References 20 publications

Selection and Optimization of Regional Economic Industrial Structure Based on Fuzzy k-Means Clustering Algorithm

Selection and Optimization of Regional Economic Industrial Structure Based on Fuzzy k-Means Clustering Algorithm

Application of $K$ -Means Clustering Algorithm in Energy Data Analysis

Tailored Design of Mesoporous PdCu Nanospheres with Different Compositions Using Polymeric Micelles

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Anti-Interference Technology of Surface Acoustic Wave Sensor Based on K-Means Clustering Algorithm

Cited by 21 publications

References 20 publications

Selection and Optimization of Regional Economic Industrial Structure Based on Fuzzy k-Means Clustering Algorithm

Selection and Optimization of Regional Economic Industrial Structure Based on Fuzzy k-Means Clustering Algorithm

Application of K -Means Clustering Algorithm in Energy Data Analysis

Tailored Design of Mesoporous PdCu Nanospheres with Different Compositions Using Polymeric Micelles

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Product

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Application of $K$ -Means Clustering Algorithm in Energy Data Analysis