Parameter simulation of multidimensional urban landscape design based on nonlinear theory

Liu, Congru; Lin, Mingsen; Rauf, Hozan Latif; Shareef, Sardar S.

doi:10.1515/nleng-2021-0049

Cited by 66 publications

(53 citation statements)

References 24 publications

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“…Otherwise, choosing noise points or outliers as the initial matrix will greatly reduce the clustering accuracy. The algorithm starts with the selection of the initial matrix [20]. Here, because the IPCM algorithm is applied to the sorting of search engine results, the interests and hobbies of users browsing the web are collected first, and the collected interests and hobbies of users are formed into a user interest model through a mathematical model.…”

Section: Methodsmentioning

confidence: 99%

Application of Sensor and Fuzzy Clustering Algorithm in Hybrid Recommender System

Zhu

2022

Journal of Sensors

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In order to solve the problem of topic drift and topic enlargement in hybrid recommendation system, a possibility C clustering algorithm based on fuzzy clustering, namely, IPCM (improved possible clustering method) algorithm, is proposed. This method improves the initial value sensitivity of PCM algorithm and introduces the user interest model into the initial matrix, so that the results obtained by the convergence of IPCM algorithm are closer to the recommended topics required by users. The recommended technology algorithm is also fused by learning from each other to form a fusion recommendation algorithm. The fusion recommendation algorithm and IPCM algorithm are applied to the result sorting, and the accuracy of the applied results is compared with that of the traditional PageRank algorithm, so as to judge the accuracy of the algorithm. The feasibility and superiority of the algorithm are verified by experiments. The experimental results show that IPCM algorithm can speed up the search for useful information and reduce the search time. Moreover, when the query range is reduced, the accuracy of the algorithm is higher than that of the traditional algorithm, which can be improved by 10% ~30%. Conclusion. This method can effectively make up for the problems of topic drift and topic enlargement in the recommendation system, with faster speed and higher accuracy.

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Section: Methodsmentioning

confidence: 99%

Application of Sensor and Fuzzy Clustering Algorithm in Hybrid Recommender System

Zhu

2022

Journal of Sensors

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“…e transfer function of neurons in the hidden layer adopts the S-type tangent function tansig. Since the S-type logarithmic function is a 0-1 function [25], which just meets the output requirements of the classifier, the transfer function of neurons in the output layer selects the S-type logarithmic function logsig [26].…”

Section: Design Of the Stored Grain Pest Identificationmentioning

confidence: 99%

Intelligent Storage Data Classification System Based on the BP Neural Network

Li¹

2022

Journal of Control Science and Engineering

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In order to solve the problem of multifeature recognition and classification of many kinds of pests, this study puts forward a method of pest feature classification using the BP neural network. Through the preprocessing of stored grain pest images, five characteristic parameters are obtained and optimized and input into the BP network for training. The experimental results show that sample 3 of flat grain thief and sample 4 of bark beetle are not well recognized. Because these two kinds of pests have small bodies and thin legs, some detailed features are eliminated after image processing, resulting in a low recognition rate. But the overall recognition rate can reach 95%. Conclusion. The experiment has obtained good recognition results. This method is accurate and effective for the classification and recognition of stored grain pests and provides a scientific basis for the scientific decision-making of controlling stored grain pests.

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“…The HOG feature detection method was proposed by the French researcher Dalal at the CVPR conference in 2005; after continuous improvement by experts and scholars, the current improved HOG feature was obtained. The usual case is to use the improved HOG feature with the improved SVM classifier to comprehensively detect pedestrians [19]. Since the gradient usually exists at the boundary, it is necessary to use many images as samples to extract the HOG features of pedestrians, which is equivalent to the description of the local area in the image.…”

Section: Pedestrian Detectionmentioning

confidence: 99%

Analysis of People Flow Image Detection System Based on Computer Vision Sensor

Yang

Wang

2022

Journal of Sensors

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In order to meet the needs of accurately grasping the situation of people in the mall at all times, the author proposes an analysis method based on computer vision for people flow image detection system. This method combines the HOG feature with the SVM classifier, detects pedestrians through dual cameras, and builds an experimental research platform for dual-camera joint detection of pedestrians. The result shows that the error rate of human flow detected by the author’s method is the lowest of 0% and the highest of 6.25%. Conclusion. This method has a good effect on the statistics of the number of people in the shopping mall and can reduce the workload of the monitoring personnel in the shopping mall.

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Parameter simulation of multidimensional urban landscape design based on nonlinear theory

Cited by 66 publications

References 24 publications

Application of Sensor and Fuzzy Clustering Algorithm in Hybrid Recommender System

Application of Sensor and Fuzzy Clustering Algorithm in Hybrid Recommender System

Intelligent Storage Data Classification System Based on the BP Neural Network

Analysis of People Flow Image Detection System Based on Computer Vision Sensor

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