Abstract:Prefabricated box culvert is a new structure in road engineering, whose health is very important to road safety. The use of acoustic emission (AE) as a detection method and the use of other improved algorithms to evaluate the damage of prefabricated box culverts are still insufficient. In this paper, two kinds of prefabricated box culverts are tested and studied, and the damage process of the box culverts is analysed based on the AE parameters of the box culvert using the traditional fuzzy C-means method (FCM)… Show more
“…where n represents the total number of samples, c represents the maximum number of clustering, m represents the weighted power index, v i represents the i-th clustering center, and u ij represents the degree to which sample j belongs to the i-th category, satisfying c i�1 u ij � 1 [10]. FCM algorithm is to find the fuzzy classification matrix U * and clustering center V * to minimize the objective function J(U, V).…”
Section: Data Mining Based On Improved Fuzzy Clusteringmentioning
In order to solve the problems of low recall rate and precision rate, high error rate, and long evaluation time in traditional evaluation methods, a comprehensive evaluation of economic management performance based on an improved fuzzy clustering algorithm is designed. The improved magnetic optimization algorithm was used to optimize the fuzzy C-mean algorithm, the improved fuzzy clustering algorithm was completed, and the improved fuzzy clustering algorithm was used to mine the economic management performance data. Using data mining findings and AHP’s weighting formula, a complete method for evaluating economic management effectiveness was developed. The BP neural network was improved using a genetic algorithm based on the index weight calculation findings, and the full-assessment model of economic management performance was constructed. Using this approach, it is possible to accurately and quickly assess the economic management performance of a company with a high rate of recall and accuracy; the error rate of a thorough assessment ranges between −3 percent and 4 percent; the average duration for an assessment is 0.81 seconds.
“…where n represents the total number of samples, c represents the maximum number of clustering, m represents the weighted power index, v i represents the i-th clustering center, and u ij represents the degree to which sample j belongs to the i-th category, satisfying c i�1 u ij � 1 [10]. FCM algorithm is to find the fuzzy classification matrix U * and clustering center V * to minimize the objective function J(U, V).…”
Section: Data Mining Based On Improved Fuzzy Clusteringmentioning
In order to solve the problems of low recall rate and precision rate, high error rate, and long evaluation time in traditional evaluation methods, a comprehensive evaluation of economic management performance based on an improved fuzzy clustering algorithm is designed. The improved magnetic optimization algorithm was used to optimize the fuzzy C-mean algorithm, the improved fuzzy clustering algorithm was completed, and the improved fuzzy clustering algorithm was used to mine the economic management performance data. Using data mining findings and AHP’s weighting formula, a complete method for evaluating economic management effectiveness was developed. The BP neural network was improved using a genetic algorithm based on the index weight calculation findings, and the full-assessment model of economic management performance was constructed. Using this approach, it is possible to accurately and quickly assess the economic management performance of a company with a high rate of recall and accuracy; the error rate of a thorough assessment ranges between −3 percent and 4 percent; the average duration for an assessment is 0.81 seconds.
“…Box culvert (BC) structure, which is used in bridging over streams, drainages, sewage pipelines, highway bridges, and other projects, is an essential part of modern infrastructure [1][2][3][4]. The investigations on the application of BC have extensively conducted in scholars, which significant advances in design, construction, and materials of BC [5].…”
Box culvert structure was an essential part of modern infrastructure. Due to the advantages of low pollution and convenient construction, the prefabricated box culvert (PBC) has been gradually utilized in engineering. However, the investigations on load bearing capacity of PBC in different reinforcement forms with same reinforcement ratios were still lack. In the present research, one PBC specimen was tested and discussed by the finite-element analysis (FEA) on load bearing capacity under four-point bending. The load bearing capacity of another three PBCs in different reinforcement forms with the same reinforcement ratios was discussed by the FEA. Results of experimental and numerical investigations showed that: (1) a number of flexural cracks were observed in the midspan bottom of upper slab of PBC, and finally shear failure was observed in bending–shear zone of upper slab of PBC; (2) the number of concrete cracking, plastic deformation of PBC, and stress of rebars reduced by increasing the area of tensile rebars in PBC with reducing the area of compressive rebars under same reinforcement ratios; (3) the ductility and load bearing capacity of PBC increased by increasing the area of tensile rebars with reducing the area of compressive rebars.
“…Over the past four decades, financial risk has had a serious impact on corporate operations and financial market stability. In China, the problem of corporate finance risk has become more and more remarkable as the socialist market economy is established [ 1 ]. In a business environment, the industry faces a very difficult and ongoing relationship and business environment where businesses do not have access to all the information they need to do business.…”
In order to solve the problem that corporate financial risks seriously affect the healthy development of enterprises, credit institutions, securities investors, and even the whole of China, the K-means clustering algorithm, the risk screening process, and the Gaussian mixture clustering algorithm, the risk screening process, are proposed; experiments have shown that although the number of high-risk companies selected by the K-means algorithm is small, only 9% of the full sample, the high-risk cluster can contain nearly 30% of the new “special treatment” companies. If the time period is extended to the next 5 years, this proportion will be higher. Finally we found that if the prediction of “special handling” events is used as the criterion for evaluating high-risk clusters, then K-means clustering can effectively screen out those risky companies that need to be treated with caution by investors. The validity of the experiment is verified.
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