With the continuous development of the network society and the frequent occurrence of network attacks, people's demand for network intrusion detection is increasing. The method of intrusion detection is basically ...
详细信息
With the continuous development of the network society and the frequent occurrence of network attacks, people's demand for network intrusion detection is increasing. The method of intrusion detection is basically to design a classifier that can distinguish the normal and abnormal data in the data stream, so as to realize the alarm of the attack behavior. This article will use the KDD99 data set in the academic circle to test the quality of intrusion detection algorithms to provide a unified performance evaluation benchmark for intrusion detection systems. This article will build a classifier based on the knn algorithm, and use the 10% training set in the data set to train the classifier, and then use the corrected test set to test the classifier performance.
By analyzing and processing user consumption behavior data on agricultural e-commerce platforms, selecting the appropriate algorithm - knn algorithm, conducting cluster analysis on these data, analyzing the consumptio...
详细信息
By analyzing and processing user consumption behavior data on agricultural e-commerce platforms, selecting the appropriate algorithm - knn algorithm, conducting cluster analysis on these data, analyzing the consumption habits of each user, and then classifying these users based on this result to understand and master different product attributes and user characteristics. Finally, predicting the market value of each product inside can provide more accurate marketing decision support for agricultural e-commerce platforms and promote their development. This study shows that the application of knn algorithm in precision marketing of agricultural product e-commerce plays an important role and can provide important reference for the formulation of marketing strategies.
Existing spectrum auction algorithms rarely consider the collusion-resistant, which decreases the spectrum allocation efficiency. In this paper, we propose a collusion-resistant spectrum auction algorithm based on K-N...
详细信息
Existing spectrum auction algorithms rarely consider the collusion-resistant, which decreases the spectrum allocation efficiency. In this paper, we propose a collusion-resistant spectrum auction algorithm based on K-Nearest Neighbor (knn) learning in small cell networks. The algorithm can satisfy the increasing requirements of broadband services, improve the utilization of spectrum and also enhance the power-transmitting efficiency in small cells. Considering the interference among small cells, the knn algorithm is used to classify all the small cells according to the small cells' geographic locations and interference radius, which can improve the collusion-resistance ability of spectrum auction and improve the spectrum allocation efficiency. Simulation results are presented to verify the effectiveness of the proposed algorithm.
The product feature set of online reviews obtained by the current product feature extraction methods has a low coverage rate of review information. In order to solve this problem, this paper proposes a method of produ...
详细信息
The product feature set of online reviews obtained by the current product feature extraction methods has a low coverage rate of review information. In order to solve this problem, this paper proposes a method of product feature extraction based on knn algorithm. We establish the classification system of product feature set firstly. Then we extract part of product features as training set manually, and according to similarity between words and the classification system, the product features of all reviews are quickly classified and extracted. At last, the PMI algorithm is used to filter and supplement it to improve the correct rate and the review information coverage rate of product feature set. Through the examples of online clothing reviews data in the Taobao platform, we prove that this method can effectively improve the review information coverage rate of product feature set.
This paper based on existing historical test case set to combined with the knn algorithm to train the classification model. The model is used to assist the design of the software performance test to obtain the optimal...
详细信息
This paper based on existing historical test case set to combined with the knn algorithm to train the classification model. The model is used to assist the design of the software performance test to obtain the optimal performance test case set. This method can provide reference for software performance test case design.
A new approach has been presented to increase the location estimation accuracy in WLAN *** Location fingerprint method base on knn algorithm,optimal parameter has not been theoretically *** studies have shown that val...
详细信息
A new approach has been presented to increase the location estimation accuracy in WLAN *** Location fingerprint method base on knn algorithm,optimal parameter has not been theoretically *** studies have shown that value of k in knn algorithm have a great impact on the positioning accuracy and should comprehensively consider the cumulative probability,the average location error distance,the complexity of the algorithm and some other *** novel technology we propose provides a practical method to select the value of k *** first uses triangulation location method based on Pass - Loss model to calculate the area where the typical measured point may exist,and then uses the traditional knn algorithm to select k closest vectors from the regional location fingerprint database which are in the triangulation location intersection district,finally calculate their estimated *** experimental results show that the new method improves the original knn algorithm and can achieve a great positioning accuracy.
A disadvantage of k-nearest neighbor(knn)algorithm is the large amount of calculation. The tree index structure can reduce the amount of calculation but it will generate an index page buffer management problem in the ...
详细信息
A disadvantage of k-nearest neighbor(knn)algorithm is the large amount of calculation. The tree index structure can reduce the amount of calculation but it will generate an index page buffer management problem in the case of the main memory capacity is limited. The traditional page replacement policy is not aimed at a tree-based high-dimensional indexing structure design features, so the page buffer hit ratio is lower. Therefore, we analyzed the characteristics of tree index structure and then designed a replacement policy based access probability distribution, the experimental results show that the replacement policy is effective.
Location-based services have been deep into all aspects of life and it provides a convenient and efficient service experience for ***,technology is relatively mature and widely used in the outdoor *** contrast,for ind...
详细信息
Location-based services have been deep into all aspects of life and it provides a convenient and efficient service experience for ***,technology is relatively mature and widely used in the outdoor *** contrast,for indoor positioning,although there are a lot of hot technology,but they are mostly insufficient lead to it is hard to *** how to improve the popularity of indoor positioning in the case of improve the positioning accuracy has bacame a hot research *** paper analyzes and studies several typical fingerprint localization algorithm,including NN,knn and Wknn,and then propose an algorithmic improvement program,it introduces signal propagation model,finds and narrows the K-gon.
With the rapid development of information technology, the concept of big data is used in information collection on different things, especially for the text classification. This paper propose an improved knn algorithm...
详细信息
ISBN:
(纸本)9781509044993
With the rapid development of information technology, the concept of big data is used in information collection on different things, especially for the text classification. This paper propose an improved knn algorithm based on clustering for the automatic classification of Web text. In addition, we find a new method to find out which text in the same category belongs to the same cluster. Finally, we classify Web text automatically and test them by using the existing and improved knn algorithm respectively. Simulation results show that the improved algorithm can significantly raise the accuracy of automatic classification.
Intrabody communication (IBC) establishes a wireless connection between devices in a Wireless Body Area Network (WBAN) by utilizing the human body as a transmission medium. The characteristics of the IBC channel are s...
详细信息
Intrabody communication (IBC) establishes a wireless connection between devices in a Wireless Body Area Network (WBAN) by utilizing the human body as a transmission medium. The characteristics of the IBC channel are significantly influenced by the geometric and biological features of the human body and tissues. This paper analyzes a dataset with experimental real subjects' data on signal loss in a galvanic IBC channel, models IBC identification using the K-Nearest Neighbors (knn) algorithm, and proposes a novel IBC WBAN architecture incorporating an identification function. The analysis of the dataset revealed that the IBC channel gain exhibits a wide range of variations depending on individual human body characteristics such as height, weight, body mass index, and body composition. Consequently, biometric identification can be leveraged within the IBC WBAN paradigm. Through modeling IBC identification on cleaned and labeled data, we demonstrated an identification accuracy of 99.9% based on the results of our modeling. The proposed IBC WBAN architecture with an integrated identification function is anticipated to enhance the application scope and accelerate the development of IBC WBANs.
暂无评论