With the requirement of reduced carbon emissions and air pollution, it has become much more important to monitor the oil quality used in heavy-duty vehicles, which have more than 2/3 transportation emissions. Some gas...
详细信息
With the requirement of reduced carbon emissions and air pollution, it has become much more important to monitor the oil quality used in heavy-duty vehicles, which have more than 2/3 transportation emissions. Some gas stations may provide unqualified fuel, resulting in uncontrollable emissions, which is a big challenge for environmental protection. Based on this focus, a gas station recognition method is proposed in this paper. Combining the cart algorithm with the DBSCAN clustering algorithm, the locations of gas stations were detected and recognized. Then, the oil quality analysis of these gas stations could be effectively evaluated from oil stability and vehicle emissions. Massive real-world data operating in Tangshan, China, collected from the Heavy-duty Vehicle Remote Emission Service and Management Platform, were used to verify the accuracy and robustness of the proposed model. The results illustrated that the proposed model can not only accurately detect both the time and location of the refueling behavior but can also locate gas stations and evaluate the oil quality. It can effectively assist environmental protection departments to monitor and investigate abnormal gas stations based on oil quality analysis results. In addition, this method can be achieved with a relatively small calculation effort, which makes it implementable in many different application scenarios.
This paper uses the numerical results of surveys sent to Huelva's (Andalusia, Spain) households to determine the degree of knowledge they have about the urban water cycle, needs, values, and attitudes regarding wa...
详细信息
This paper uses the numerical results of surveys sent to Huelva's (Andalusia, Spain) households to determine the degree of knowledge they have about the urban water cycle, needs, values, and attitudes regarding water in an intermediary city with low water stress. In previous research, we achieved three different households' clusters. The first one grouped households with high knowledge of the integral water cycle and a positive attitude to smart devices at home. The second cluster described households with low knowledge of the integral water cycle and high sensitivity to price. The third one showed average knowledge and predisposition to have a closer relationship with the water company. This paper continues with this research line, applying Classification and Regression Trees (cart) to determine which hierarchy of variables/factors/independent components obtained from the surveys are the decisive ones to predict the range of household water consumption in Huelva. Positive attitudes towards improved cleaning habits for personal or household purposes are the highest hierarchy component to predict the water consumption range. Second in the hierarchy, the variable Knowledge Global Score about the integral urban water cycle, associated with water literacy, also contributes to predicting the water consumption range. Together with the three clusters obtained previously, these results will allow us to design water demand management strategies (WDM) fit for purpose that enable Huelva's households to use water more efficiently.
In order to address one of the most challenging problems in hospital management - patients' absenteeism without prior notice - this study analyses the risk factors associated with this event. To this end, through ...
详细信息
In order to address one of the most challenging problems in hospital management - patients' absenteeism without prior notice - this study analyses the risk factors associated with this event. To this end, through real data from a hospital located in the North of Portugal, a prediction model previously validated in the literature is used to infer absenteeism risk factors, and an explainable model is proposed, based on a modified cart algorithm. The latter intends to generate a human-interpretable explanation for patient absenteeism, and its implementation is described in detail. Furthermore, given the significant impact, the COVID-19 pandemic had on hospital management, a comparison between patients' profiles upon absenteeism before and during the COVID-19 pandemic situation is performed. Results obtained differ between hospital specialities and time periods meaning that patient profiles on absenteeism change during pandemic periods and within specialities.
Ride-hailing application price decisions are frequently considered biased and therefore are receiving more attention. Electronic (e)-hailing providers use the machine learning reinforcement model (RL) to build their d...
详细信息
Ride-hailing application price decisions are frequently considered biased and therefore are receiving more attention. Electronic (e)-hailing providers use the machine learning reinforcement model (RL) to build their dynamic pricing (DP) strategy to charge consumers. Nevertheless, the associated pricing issues in e-hailing potentially jeopardise this flourishing industry with a more significant long-term effect if left unresolved. Upon increased demand, the DP strategies assist the e-hailing systems with price surging, the unreasonable surging of price is unexpected by e-hailing users and deters them from using e-hailing services. A drawback of the existing RL DP algorithm is that does not consider surrounding factors before surging the price. Hence, this study aimed to address the underlying pricing issues through a hybrid pricing model using classification and regression tree (cart) supervised learning. A hybrid pricing algorithm was developed to demonstrate the enhanced model has edge over the existing model. The current e-hailing RL based algorithm was compared against the SL's cart enhanced pricing algorithm with cross-validation using centrality analysis results. The test results shows that the hybrid pricing algorithm could address DP pricing issues by optimising e-hailing prices to provide its consumers with impartial pricing and remuneration. The proposed model can be a good theoretical reference for further studies which can also be applied to other industries such as Airlines, Tourism where DP is in used.
IPTV is a new multimedia service over the Internet. In order to improve the quality of IPTV service and the user's satisfaction, telecom operators are interested in studying and improving user's Quality of Exp...
详细信息
ISBN:
(纸本)9781509028610
IPTV is a new multimedia service over the Internet. In order to improve the quality of IPTV service and the user's satisfaction, telecom operators are interested in studying and improving user's Quality of Experience (QoE). In this paper, we study the relationship between the viewing records from IPTV set-top box and the user's QoE based on IPTV service. Firstly, data processing is performed. After the procedure, the important attributes influencing QoE are selected. Then we propose a new attribute called user's viewing custom from the user's point of view. We also create a mapping between viewing time ratio and user's QoE for subjective video quality evaluation. In addition, we improve the cart algorithm with the idea of weighted mean. Experimental results show that the proposed methods can indeed improve the prediction accuracy of QoE model when comparing with original method.
Utilized the C5.0 and cart algorithm of the data mining technique,we researched the income satisfaction of the countryside people,taking He bei province as an example,modeling on the survey data acquired from the &quo...
详细信息
Utilized the C5.0 and cart algorithm of the data mining technique,we researched the income satisfaction of the countryside people,taking He bei province as an example,modeling on the survey data acquired from the "New Rural Construction" ***,this paper analyzed the influencing factors of income satisfaction,and additionally analyzed the village factor and the personal *** the modeling,three variable importance ranks were obtained including an integrated,a village factors’ and a personal factors’.Furthermore,decision tree of income satisfaction of villagers were *** we got conclusion that the villages’ facility has the strongest affection to the income *** social security,government subsidies and the farming industry of the villages also influence the income *** last,based on the problems reflected by the questionnaires and the research results,the corresponding policy proposals of raising the farmers’ income were put forward.
暂无评论