Evaluation method for gas pre-extraction status in coal seam boreholes based on semi-supervised learning by YAN Li, WEN Hu, WANG Zhenping, JIN Yongfei

Subjects: Get full text

Video Refereeing Model of Soccer Match Based on Fuzzy Clustering and Cuckoo Optimization Algorithm by Ting Wang, Jinglong Geng, Jing Wang, Xiao Yan

“…The enhanced algorithm model, enhanced cuckoo-fuzzy C-mean algorithm model, cuckoo-fuzzy C-mean algorithm model, and fuzzy C-mean algorithm model had delineation effects of 0.80, 0.72, 0.70, and 0.61, in that order. …”
Get full text

Robust FCM Algorithm with Local and Gray Information for Image Segmentation by Hanane Barrah, Abdeljabbar Cherkaoui, Driss Sarsri

“…The FCM (fuzzy c-mean) algorithm has been extended and modified in many ways in order to solve the image segmentation problem. …”
Get full text

Intrusion Detection System Based on Decision Tree and Clustered Continuous Inputs by Adel Issa

“…The purpose of this paper is to use ID3 algorithm for IDS and extend it to deal not only with discreet values, but also with continuous ones, by using K_mean algorithm to partition each continuous attribute values to three clusters. …”
Get full text

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification by Guizhou Wang, Jianbo Liu, Guojin He

“…Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy.…”
Get full text

Energy Services Demand Forecasting Combined with Feature Preferences and Bidirectional Long- and Short-Term Memory Networks by KANG Feng, TAN Huochao, SU Liwei, JIAN Donglin, WANG Shuai, QIN Hao, ZHANG Yongjun

“…The methodology includes introducing a sampling algorithm to solve the class imbalance problem in the data on the basis of analysing the user energy service data, reducing the dimensionality of the data based on an autoencoder to ensure efficient clustering of the K-mean algorithm, constructing a feature selection algorithm based on a lightweight gradient lifting machine to filter the effective features and improve the training efficiency of the prediction model, and establishing a bidirectional long- and short-term memory neural network multi-label predicting model based on an attentional mechanism to refine the user’s energy service demand. …”
Get full text

Identification and evaluation of the effective criteria for detection of congestion in a smart city by Anita Mohanty, Subrat Kumar Mohanty, Bhagyalaxmi Jena, Ambarish G. Mohapatra, Ahmed N. Rashid, Ashish Khanna, Deepak Gupta

“…In the simulation of urban mobility (SUMO) simulator, a transport network is created and parameters of vehicles facing congestion are taken to extract the key parameter by using the k‐means clustering technique and mathematical mean algorithm. This parameter is utilized in analytical hierarchy process to detect the highest priorities parameter and based on that the congestion is detected in particular lane. …”
Get full text

Detection method of slight bruises of apples based on hyperspectral imaging and RELIEF-extreme learning machine by ZHANG Meng, LI Guanghui

“…Then, based on full wavebands and characteristic wavebands, an extreme learning machine (ELM) model was built, as comparison with support vector machine (SVM) and K- mean algorithm. The results showed that the recognition accuracy of ELM model for the test set based on the full wavebands was 94.44%, and the accuracy of the Re-ELM model based on the characteristic wavebands was 96.67%, and the accuracy of the Re-SVM and Re-K mean models for the characteristic wavebands were 92.22% and 91.67%, respectively, which demonstrated that the Re-ELM was a more effective method for the bruise apple classification. …”
Get full text

Analyses of poverty indicators using PPI methodology by T. Merkulova, D. Kosiashvili

“…Developing the model was carried out using machine learning methods in several steps: 1) data processing and statistical analyses; 2) selection of significant indicators by the classification model; 3) clustering by k-mean algorithm; 4) hierarchical clustering; 5) comparing outcomes of modeling and interpretation of results. …”
Get full text

Measurements and Characterization for Millimeter-Wave Massive MIMO Channel in High-Speed Railway Station Environment at 28 GHz by Shuangde Li, Yuanjian Liu, Leke Lin, Qi Sun

“…And they are processed by using the K-mean algorithm. In addition, propagation characteristics are simulated based on the improved ray tracing method of shooting and bouncing ray tracing/image (SBR/IM). …”
Get full text

Topology Optimization of Offshore Wind Power Collection System Considering Actual Carrying Capacity of Submarine Cables by Jing YE, Junwen CAI, Lei ZHANG, Guanghao ZHOU, Jiehui HE, Xue ZHAI

“…Firstly, the wind turbines were divided into clustered partitions using the fuzzy C-mean algorithm, and the power collection system topology was divided into intra-partition and extra-partition topology optimization. …”
Get full text

Enhancing Fuzzy C-Means Clustering with a Novel Standard Deviation Weighted Distance Measure by Ahmed Husham Mohammed, Marwan Abdul Hameed Ashour

“…The aim of this paper is to present a new approach to address the Fuzzy C Mean algorithm, which is considered one of the most important and famous algorithms that addressed the phenomenon of uncertainty in forming clusters according to the overlap ratios. …”
Get full text

Big data technology for teaching quality monitoring and improvement in higher education - joint K-means clustering algorithm and Apriori algorithm by Yang Li, Haiyu Zhang

“…The study first analyzes the teaching quality monitoring and evaluation indexes using the K-mean algorithm. Then the association rule mining algorithm is utilized to mine the data in the teaching quality monitoring indicators with association rules on the basis of the obtained cluster analysis. …”
Get full text

Integrating Cognitive Intelligence and VANET for Effective Traffic Congestion Detection in Smart Urban Mobility by Anita Mohanty, Ambarish G. Mohapatra, Subrat Kumar Mohanty, Tiansheng Yang, Rajkumar Singh Rathore, Ahmed Alkhayyat, Deepak Gupta

“…These parameters are processed using FKM clustering and a mathematical mean algorithm to identify key congestion indicators. …”
Get full text

Pemodelan K-Means Pada Penentuan Predikat Kelulusan Mahasiswa STMIK Palangka Raya by Lili Rusdiana, Sam'ani Sam'ani

“…Modeling using the K-Means is one of the concepts to be able to classify the data, so the use of K-Means algorithm can be a reference for the development of a modeling study, especially regarding data mining.…”
Get full text

Design of smart agriculture based on big data and Internet of things by Chunling Li, Ben Niu

“…The crop growth curve is simulated and compared with improved K-means algorithm and the original k-means algorithm in the experimental analysis. …”
Get full text

Extension Distance-Driven K-Means: A Novel Clustering Framework for Fan-Shaped Data Distributions by Xingsen Li, Hanqi Yue, Yaocong Qin, Haolan Zhang

“…The K-means algorithm utilizes the Euclidean distance metric to quantify the similarity between data points and clusters, with the fundamental objective of assessing the relationship between points. …”
Get full text

Balanced Cluster Head Selection Based on Modified -Means in a Distributed Wireless Sensor Network by Sasikumar Periyasamy, Sibaram Khara, Shankar Thangavelu

“…A modified k -means ( Mk- means) algorithm for clustering was proposed which includes three cluster heads (simultaneously chosen) for each cluster. …”
Get full text

An Improved Integrated Clustering Learning Strategy Based on Three-Stage Affinity Propagation Algorithm with Density Peak Optimization Theory by Limin Wang, Wenjing Sun, Xuming Han, Zhiyuan Hao, Ruihong Zhou, Jinglin Yu, Milan Parmar

“…DPKT-AP combined the ideology of integrated clustering with the AP algorithm, by introducing the density peak theory and k-means algorithm to carry on the three-stage clustering process. …”
Get full text

Combination of Transformed-means Clustering and Neural Networks for Short-Term Solar Radiation Forecasting by M. Ghayekhloo, M. B. Menhaj

“…The proposed Transformed-Means clustering method is based on inverse data transformation and K-means algorithm that presents moreaccurate clustering results when compared to the K-Means algorithm; its improved version and also otherpopular clustering algorithms. …”
Get full text