
Chi-Hua ChenFuzhou University · College of Mathematics and Computer Science
Chi-Hua Chen
Doctor of Philosophy
About
135
Publications
29,656
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2,228
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Introduction
Chi-Hua Chen is a distinguished professor (Minjiang scholar and Qishan scholar) for the College of Mathematics and Computer Science of Fuzhou University. He has published over 250 journal articles, conference articles, and patents. He serves as an editor for several international journals. His recent research interests include Internet of things, big data, deep learning, cloud computing, cellular networks, data mining, intelligent transportation systems, network security, healthcare systems, augmented reality, e-learning systems, and digital marketing.
Additional affiliations
February 2017 - present
August 2016 - January 2017
August 2016 - present
Chunghwa Telecom Co., Ltd.
Position
- Research Associate
Education
September 2010 - November 2013
Publications
Publications (135)
This study proposes Random Neural Networks (RNNs) to randomly train several Neural Network (NN) models for the promotion of traditional NN. Moreover, an Arrival Time Prediction Method (ATPM) based on RNNs is proposed to predict the stop-to-stop travel time for motor carriers. In experiments, the results showed that the average accuracies of RNNs ar...
In order to generate a probability density function (PDF) for fitting the probability distributions of practical data, this study proposes a deep learning method which consists of two stages: (1) a training stage for estimating the cumulative distribution function (CDF) and (2) a performing stage for predicting the corresponding PDF. The CDFs of co...
Information and communication technologies have improved the quality of intelligent transportation systems (ITS). By estimating from cellular floating vehicle data (CFVD) is more cost-effective, and easier to acquire than traditional ways. This study proposes a cell probe (CP)-based method to analyse the cellular network signals (e.g., call arrival...
In recent years, intelligent transportation system (ITS) techniques have been widely exploited to enhance the quality of public services. As one of the worldwide leaders in recycling, Taiwan adopts the waste collection and disposal policy named “trash doesn't touch the ground”, which requires the public to deliver garbage directly to the collection...
To achieve accurate traffic forecasting, previous research has employed inner and outer aggregation for information aggregation, and attention mechanisms for heterogeneous spatiotemporal dependency learning, which results in inefficient model learning. While learning efficiency is critical due to the need for updating frequently the model to allevi...
The technology that is most likely to change the corporate world in the next ten years is not social networks, Big Data, cloud computing, robots, not even artificial intelligence, but blockchain [...]
The Workshop Program of the Association for the Advancement of Artificial Intelligence’s Thirty-Sixth Conference on Artificial Intelligence was held virtually from February 22 – March 1, 2022. There were thirty-nine workshops in the program: Adversarial Machine Learning and Beyond, AI for Agriculture and Food Systems, AI for Behavior Change, AI for...
Accurate travel time prediction (TTP) is a significant aspect in the intelligent transportation system (ITS). Travel times of certain road segments explicitly reflect the traffic conditions of those sections. Effective TTP of road segments is instrumental in route planning, traffic control, and traffic management. However, the accuracy of TTP is gr...
Aiming for accurate data-driven predictions for the passenger walking time, this study proposes a novel neuron-network-based mixture probability (NNBMP) model with repetition learning (RL) to estimate the probability density distribution of passenger walking time (PWT) in the metro station. Our conducted experiments for Fuzhou metro stations demons...
August 22-25, 2022, Espoo, Finland Summary The advent of sensor-rich smart devices (e.g., smartphones, smart watches, smart glasses) has enabled plenty of mobile sensing applications and services, such as indoor positioning and navigation, activity recognition, context recognition, invasion detection. Recently, deep learning has become very popular...
Wheelset fault detection with high accuracy is challenging due to poor image quality. Specifically, the wheelset images are collected dynamically outdoors and suffer from diffuse reflection and environmental interference. Thus, the images contain light stripe adhesions (light flairs) and local fractures to be inpainted. The existing inpainting mode...
Intelligent equipment within the Internet of things (IoT) carries out massive, frequent, and persistent data communication, making privacy protection particularly critical. Different from regular encryption methods or neural networks, this study proposes a de-correlation neural network (DeCNN) which synchronously realizes the estimation and privacy...
The graph convolution network (GCN), whose flexible convolution kernels perfectly adapt to the complex topology of the road network, has gradually dominated the spatiotemporal dependency learning of traffic flow data. Defining and learning the spatiotemporal characteristics and relationships of the traffic network efficiently and accurately, which...
In recent years, some traffic information prediction methods have been proposed to provide the precise information of travel time, vehicle speed, and traffic flow for highways. However, big errors may be obtained by these methods for urban roads or the alternative roads of highways. Therefore, this study proposes a travel time prediction method bas...
This research proposes a pre-signed response method based on online certificate status protocol (OCSP) request prediction. A request prediction method is proposed to analyse and predict potential volumes of certificate signing requests for a given time or period, so that responses to the requests can be generated and pre-signed during off-peak hour...
It is of great reference significance to exploring spatial dependence of urban traffic activities and researching internal causes of regional traffic state changes for road network optimization and residents’ travel behavior analysis. Based on trajectory data of taxis in Ningbo city of China, this study calculates average driving speed of taxis in...
It is a conference proceeding: 7th International Conference on Machinery, Material Science and Engineering Application (MMSE) 2021 24-25 July 2021, Hangzhou Radisson Hotel Platinum, Hangzhou, China
During the detection of maritime targets, the jitter of the shipborne camera usually causes the video instability and the false or missed detection of targets. Aimed at tackling this problem, a novel algorithm for maritime target detection based on the electronic image stabilization technology is proposed in this study. The algorithm mainly include...
As the network technologies have rapidly developed in recent years, many Internet of Things (IoT) based services and applications have walked into our daily lives; one of these is the medical information system. In the early days, medical information was recorded and stored in article form. It contains a patient identity background, past medical hi...
Global routing is an important link in very large scale integration (VLSI) design. As the best model of global routing, X-architecture Steiner minimal tree (XSMT) has a good performance in wire length optimization. XSMT belongs to non-Manhattan structural model, and its construction process cannot be completed in polynomial time, so the generation...
Recurrent neural networks (RNNs) have been effective methods for time series analyses. The network representation learning model and method based on deep learning can excellently analyze and predict the community structure of social networks. However, the node relationships of complex social networks in the real world often change over time. Theref...
The most important parts of Taiwan's agriculture are animal husbandry and the pig industry, of which the output value reached NT$75.6 billion in 2017. Taiwan has a high technical level of pig raising. However, practical pig‐raising skills rely mainly on the inheritance of mentoring experience. The livestock and pig breeding industry in Taiwan has n...
Sensing navigational environment represented by navigation marks is an important task for unmanned ships and intelligent navigation systems, and the sensing can be performed by recognizing the images from a camera. In order to improve the image recognition accuracy, this paper combined a contour accentuation algorithm into a multiple scale attentio...
Equitable access to efficient medical services via public transport has always been one of the most important issues of healthcare in urban development. To accurately measure the urban public transport accessibility to medical services (PTAMS), this research proposes a hybrid assessment method based on multiple public-transport related indicators,...
Intelligent transportation system (ITS) contributes to allocate transportation resources, from citywide ones to nationwide, more efficiently with the help of algorithms. Due to the fact that the ITS is a quite comprehensive field, it is necessary for researchers to have a better understanding of dominant methods and which one is proper for the targ...
Feature selection (FS) plays an important role in the machine learning (ML) field. Since FS solves the problem of dimensional explosion in ML very well, more and more people are paying attention to FS. Not only that, but this technique also takes advantage of the computational complexities and time reductions. Inspired by the points mentioned above...
The global environment has become more polluted due to the rapid development of industrial technology. However, the existing machine learning prediction methods of air quality fail to analyze the reasons for the change of air pollution concentration because most of the prediction methods take more focus on the model selection. Since the framework o...
Dimensionality reduction plays an important role in the data processing of machine learning and data mining, which makes the processing of high-dimensional data more efficient. Dimensionality reduction can extract the low-dimensional feature representation of high-dimensional data, and an effective dimensionality reduction method can not only extra...
Purpose
The crowdfunding market has experienced rapid growth in recent years. However, not all projects are successfully financed because of information asymmetries between the founder and the providers of external finance. This shortfall in funding has made factors that lead to successful fundraising, a great interest to researchers. This study dr...
Diabetic retinopathy (DR) is a major reason for the increased visual loss globally, and it became an important cause of visual impairment among people in 25-74 years of age. The DR significantly affects the economic status in society, particularly in healthcare systems. When timely treatment is provided to the DR patients, approximately 90% of pati...
Graph embedding is an effective yet efficient way to convert graph data into a low dimensional space. In recent years, deep learning has applied on graph embedding and shown outstanding performance. Adjacency matrix is often taken as the storage data structure of graph. However, there are the problems of insufficient spatial proximity information i...
The submission deadline is September 30, 2020 and the expected publication date is March 30, 2021.
The details of the special issue can be found from the link https://think.taylorandfrancis.com/special_issues/statistical-big-data/.
The guest editors solicit results mainly concerning recent advances and challenges in both the theory and applicati...
In recent years, deep neural networks have been applied to obtain high performance of prediction, classification, and pattern recognition. However, the weights in these deep neural networks are difficult to be explained. Although a linear regression method can provide explainable results, the method is not suitable in the case of input interaction....
Massive amount of water level data has been collected by using Internet of Things (IoT) techniques in the Yangtze River and other rivers. In this paper, utilizing these data to construct deep neural network models for water level prediction is focused. To achieve higher accuracy, both the factors of time and locations of data collection sensors are...
This editorial introduces the Special Issue, entitled “Deep Learning Applications with Practical Measured Results in Electronics Industries”, of Electronics. Topics covered in this issue include four main parts: (I) environmental information analyses and predictions, (II) unmanned aerial vehicle (UAV) and object tracking applications, (III) measure...
Recognizing objects from camera images is an important field for researching smart ships and intelligent navigation. In sea transportation, navigation marks indicating the features of navigational environments (e.g. channels, special areas, wrecks, etc.) are focused in this paper. A fine-grained classification model named RMA (ResNet-Multiscale-Att...
The interpolation of fine-grained air quality has significant prospects in the area of air quality monitoring. The solution to this problem can effectively monitor the air quality of the areas by sparse air quality monitoring stations, so as to reduce the monitoring cost. Most of the existing researches are to solve the problem of air quality monit...
With the fast development of the mobile Internet, the online platforms of social networks have rapidly been developing for the purpose of making friends, sharing information, etc. In these online platforms, users being related to each other forms social networks. Literature reviews have shown that social networks have community structure. Through t...
With the recent rapid increase in the number of motor vehicles on roads, traffic accidents have increased, and emergency reporting processes have become essential. In this paper, a key agreement protocol for a real-time traffic sharing system is proposed for Vehicular Ad-Hoc Networks (VANETs), in which a broadcast center authenticates the legitimac...
In recent years, the rapid development of industrial technology has been accompanied by serious environmental pollution. In the face of numerous environmental pollution problems, particulate matter (PM2.5) which has received special attention is rich in a large amount of toxic and harmful substances. Furthermore, PM2.5 has a long residence time in...
This editorial introduces the Special Issue, entitled “Deep Learning (DL) Techniques for Agronomy Applications”, of Agronomy. Topics covered in this issue include three main parts: (I) DL-based image recognition techniques for agronomy applications, (II) DL-based time series data analysis techniques for agronomy applications, and (III) behavior and...
This study proposes a mobile positioning method that adopts recurrent neural network algorithms to analyze the received signal strength indications from heterogeneous networks (e.g., cellular networks and Wi-Fi networks) for estimating the locations of mobile stations. The recurrent neural networks with multiple consecutive timestamps can be applie...
Music is a series of harmonious sounds well arranged by musical elements including rhythm, melody, and harmony (RMH). Since music digitalization has resulted in a wide variety of new musical applications used in daily life, the use of music genre classification (MGC), especially MGC automation, is increasingly playing a key role in the development...
To generate a probability density function (PDF) for fitting probability distributions of real data, this study proposes a deep learning method which consists of two stages: (1) a training stage for estimating the cumulative distribution function (CDF) and (2) a performing stage for predicting the corresponding PDF. The CDFs of common probability d...
This study proposes a mobile positioning method which adopts recurrent neural network algorithms to analyze the received signal strength indications from heterogeneous networks (e.g., cellular networks and Wi-Fi networks) for estimating the locations of mobile statioThis study proposes a mobile positioning method which adopts recurrent neural netwo...
This editorial introduces the special issue, entitled “Applications of Internet of Things”, of Symmetry. The topics covered in this issue fall under four main parts: (I) communication techniques and applications, (II) data science techniques and applications, (III) smart transportation, and (IV) smart homes. Four papers on sensing techniques and ap...
This editorial introduces the special issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITS), (II) location-based services (LBS), and (III) sensing techniques and applications. Three papers on ITS are...
This study examined medical students’ perceptions towards medical errors and the policy of the hospital within the internship curriculum, and explored how aspects of personality traits of medical students relate to their attitude toward medical errors. Based on the theory of the Five-Factor-Model (FFM) and related literature review, this study adop...
This study proposes an exercise fatigue detection model based on real-time clinical data which includes time domain analysis, frequency domain analysis, detrended fluctuation analysis, approximate entropy, and sample entropy. Furthermore, this study proposed a feature extraction method which is combined with an analytical hierarchy process to analy...
In recent years, governments applied intelligent transportation system (ITS) technique to provide several convenience services (e.g., garbage truck app) for residents. This study proposes a garbage truck fleet management system (GTFMS) and data feature selection and data clustering methods for travel time prediction. A GTFMS includes mobile devices...
In this study, a cloud service optimisation model is presented for resource adaptation control, in which the cost to the user, various levels of virtual machine efficacy, and rental price are considered. A cloud service middleware that supports flexible web services by using heterogeneous platforms is proposed. Developers can conveniently register...
This study adopts a fuel consumption estimation method to measure the consumed fuel quantity of each vehicle speed interval (i.e., a cost function) in accordance with individual behaviors. Furthermore, a mobile app is designed to consider the best responses of other route plan apps (e.g., the shortest route plan app and the fast route plan app) and...
This study proposes a classification algorithm based on ensemble neural networks. In the training phase, the proposed algorithm uses a random number of training data to develop multiple random artificial neural network (ANN) models until those ANN models converge. Those models with lower accuracy than the threshold are filtered out. The remaining h...
An intelligent tour service system including an augmented reality (AR) tour-sharing Application (APP) and a query-answering server was developed in this study to promote tourist attractions involving local Hakka culture in Thailand. Subsequently, use of this APP to navigate Hakka culture tourist attractions in Thailand was observed. The novel rando...
This study proposes a fuel consumption estimation system and method with lower cost. On-board units can report vehicle speed, and user devices can send fuel information to a data analysis server. Then the data analysis server can use the proposed fuel consumption estimation method to estimate the fuel consumption based on driver behaviours without...
In cellular networks, call blocking causes lower customer satisfaction and economic loss. Therefore, the channel allocation for call block avoidance is an important issue. This study proposes a mechanism that considers the real-time traffic information (e.g., traffic flow and vehicle speed) and the user behavior (e.g., call inter-arrival time and c...
The service-oriented architecture (SOA) is a popular technology that provides advantages for people designing an integrated business information system for consumer services. Web services (WSs) are basic tools to provide flexibility and crossing heterogeneous platforms when implementing a SOA. However, WSs still have some limitations. For instance,...
With the rise and development of information technology (IT) services, the amount of data generated is rapidly increasing. Data from many different places are inconsistent. Data capture, storage and analysis have major challenges. Most data analysis methods are unable to handle such large amounts of data. Many studies employ neural networks, mostly...
Commercial vehicle operation (CVO) has been a popular application of intelligent transportation systems. Location determination and route tracing of an on-board unit (OBU) in a vehicle is an important capability for CVO. However, large location errors from global positioning system (GPS) receivers may occur in cities that shield GPS signals. Theref...
In recent years, the improvement of cloud computing and mobile computing techniques has led to the availability of a variety of mobile applications (‘apps’) in the app store. For instance, a garbage truck app that can provide the immediate location of a garbage truck, the location of collection points, and forecasted arrival times of garbage trucks...
Traffic information estimation and forecasting methods based on cellular floating vehicle data (CFVD) are proposed to analyze the signals (e.g., handovers (HOs), call arrivals (CAs), normal location updates (NLUs) and periodic location updates (PLUs)) from cellular networks. For traffic information estimation, analytic models are proposed to estima...
Fast growth of the economy and technology upgrades have led to improvements in the quality of traditional transport systems. As such, the use of intelligent transportation systems (ITS) has become more and more popular. The implementation and improvement of real-time traffic information systems are an important parts of ITS. Compared with other tra...