Taoying Li
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View article: Fault Detection and Diagnosis of Rolling Bearings in Automated Container Terminals Using Time–Frequency Domain Filters and CNN-KAN
Fault Detection and Diagnosis of Rolling Bearings in Automated Container Terminals Using Time–Frequency Domain Filters and CNN-KAN Open
In automated container terminals (ACTs), rolling bearings of equipment serve as crucial power transmission components, and their performance directly determines the operational efficiency, reliability, and service life of the entire equipm…
View article: Sparse Ship Wake Detection in Rsi Using Data Augmentation-Based Deep Learning Architecture
Sparse Ship Wake Detection in Rsi Using Data Augmentation-Based Deep Learning Architecture Open
View article: Sparse Ship Wake Detection in Rsi Using Data Augmentation-Based Deep Learning Architecture
Sparse Ship Wake Detection in Rsi Using Data Augmentation-Based Deep Learning Architecture Open
View article: Integrated Scheduling of Handling Equipment in Automated Container Terminal Considering Quay Crane Faults
Integrated Scheduling of Handling Equipment in Automated Container Terminal Considering Quay Crane Faults Open
Quay cranes (QCs) play a vital role in automated container terminals (ACTs), and once a QC malfunctions, it will seriously affect the operation efficiency of ships being loaded and unloaded by the QC. In this study, we investigate an integ…
View article: Multi-Scale Residual Depthwise Separable Convolution for Metro Passenger Flow Prediction
Multi-Scale Residual Depthwise Separable Convolution for Metro Passenger Flow Prediction Open
Accurate prediction of metro passenger flow helps operating departments optimize scheduling plans, alleviate passenger flow pressure, and improve service quality. However, existing passenger flow prediction models tend to only consider the…
View article: Cas2s: A Generic Deep Learning Model for Short-Term Metro Passenger Flow Prediction
Cas2s: A Generic Deep Learning Model for Short-Term Metro Passenger Flow Prediction Open
View article: GW-DC: A Deep Clustering Model Leveraging Two-Dimensional Image Transformation and Enhancement
GW-DC: A Deep Clustering Model Leveraging Two-Dimensional Image Transformation and Enhancement Open
Traditional time-series clustering methods usually perform poorly on high-dimensional data. However, image clustering using deep learning methods can complete image annotation and searches in large image databases well. Therefore, this stu…
View article: PM2.5 Concentration Prediction Based on CNN-BiLSTM and Attention Mechanism
PM2.5 Concentration Prediction Based on CNN-BiLSTM and Attention Mechanism Open
The concentration of PM2.5 is an important index to measure the degree of air pollution. When it exceeds the standard value, it is considered to cause pollution and lower the air quality, which is harmful to human health and can cause a va…
View article: SRPM–CNN: a combined model based on slide relative position matrix and CNN for time series classification
SRPM–CNN: a combined model based on slide relative position matrix and CNN for time series classification Open
Research on the time series classification is gaining an increased attention in the machine learning and data mining areas due to the existence of the time series data almost everywhere, especially in our daily work and life. Recent studie…
View article: Time Series Clustering Model based on DTW for Classifying Car Parks
Time Series Clustering Model based on DTW for Classifying Car Parks Open
An increasing number of automobiles have led to a serious shortage of parking spaces and a serious imbalance of parking supply and demand. The best way to solve these problems is to achieve the reasonable planning and classify management o…
View article: Mammographic Classification Based on XGBoost and DCNN With Multi Features
Mammographic Classification Based on XGBoost and DCNN With Multi Features Open
The classification of benign and malignant masses in mammograms by Computer-Aided Diagnosis (CAD) is one of the most difficult and important tasks in the development of CAD systems. This classification has commonly been automated by extrac…
View article: A Hybrid CNN-LSTM Model for Forecasting Particulate Matter (PM2.5)
A Hybrid CNN-LSTM Model for Forecasting Particulate Matter (PM2.5) Open
PM2.5 is one of the most important pollutants related to air quality, and the increase of its concentration will aggravate the threat to people's health. Therefore, the prediction of surface PM2.5 concentration is of great significance to …
View article: The Temperature Forecast of Ship Propulsion Devices from Sensor Data
The Temperature Forecast of Ship Propulsion Devices from Sensor Data Open
The big data from various sensors installed on-board for monitoring the status of ship devices is very critical for improving the efficiency and safety of ship operations and reducing the cost of operation and maintenance. However, how to …
View article: Forecasting of Maritime Traffic Accident based on Residual Error Unbiased Grey Forecast Model
Forecasting of Maritime Traffic Accident based on Residual Error Unbiased Grey Forecast Model Open
In order to enhance the safety of maritime transportation and improve the accuracy of maritime traffic accident prediction, an unbiased grey forecast model based on residual error is applied to predict maritime traffic accident. Based on t…
View article: Author Cooperation Network in Biology and Chemistry Literature during 2014–2018: Construction and Structural Characteristics
Author Cooperation Network in Biology and Chemistry Literature during 2014–2018: Construction and Structural Characteristics Open
How to explore the interaction between an individual researcher and others in scientific research, find out the degree of association among individual researchers, and evaluate the contribution of researchers to the whole according to the …
View article: Combined Recommendation Algorithm Based on Improved Similarity and Forgetting Curve
Combined Recommendation Algorithm Based on Improved Similarity and Forgetting Curve Open
The recommendation algorithm in e-commerce systems is faced with the problem of high sparsity of users’ score data and interest’s shift, which greatly affects the performance of recommendation. Hence, a combined recommendation algorithm ba…
View article: Identification of S-nitrosylation sites based on multiple features combination
Identification of S-nitrosylation sites based on multiple features combination Open
View article: Recognition of Protein Pupylation Sites by Adopting Resampling Approach
Recognition of Protein Pupylation Sites by Adopting Resampling Approach Open
With the in-depth study of posttranslational modification sites, protein ubiquitination has become the key problem to study the molecular mechanism of posttranslational modification. Pupylation is a widely used process in which a prokaryot…
View article: Pricing Strategies of Logistics Distribution Services for Perishable Commodities
Pricing Strategies of Logistics Distribution Services for Perishable Commodities Open
The problem of pricing distribution services is challenging due to the loss in value of product during its distribution process. Four logistics service pricing strategies are constructed in this study, including fixed pricing model, fixed …
View article: Support Vector Machine Classifier for Accurate Identification of piRNA
Support Vector Machine Classifier for Accurate Identification of piRNA Open
Piwi-interacting RNA (piRNA) is a newly identified class of small non-coding RNAs. It can combine with PIWI proteins to regulate the transcriptional gene silencing process, heterochromatin modifications, and to maintain germline and stem c…
View article: Co-Occurrence Network of High-Frequency Words in the Bioinformatics Literature: Structural Characteristics and Evolution
Co-Occurrence Network of High-Frequency Words in the Bioinformatics Literature: Structural Characteristics and Evolution Open
The subjects of literature are the direct expression of the author’s research results. Mining valuable knowledge helps to save time for the readers to understand the content and direction of the literature quickly. Therefore, the co-occurr…
View article: Port Cargo Throughput Forecasting Based On Combination Model
Port Cargo Throughput Forecasting Based On Combination Model Open
Port cargo throughput forecasting is an essential issue in port planning and management.Owing to that cargo throughput is affected by many factors; a single model is often difficult to get an accurate prediction.On the basis of discussing …
View article: Research on Load Balancing and Database Replication based on Linux
Research on Load Balancing and Database Replication based on Linux Open
With development of computer and network technology, people access to the Internet grew exponentially, data become an integral part of people's life.More and more companies begin to use load balancing and database replication technology, t…