Transformer-based correction scheme for short-term bus load prediction in holidays

To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduce complexity and capture inherent characteristics more effectively.Gated residual connections are then employed to selectively propagate salient features across layers,while an attention mechanism focuses on identifying prominent patterns in multivariate time-series data.Ultimately,a pre-trained structure is incorporated to reduce computational complexity.Experimental results based on extensive data show that the proposed scheme achieves improved prediction accuracy over comparative algorithms by at least 32.00%consistently across all buses evaluated,and the fitting effect of holiday load curves is outstanding.Meanwhile,the pre-trained structure drastically reduces the training time of the proposed algorithm by more than 65.75%.The proposed scheme can efficiently predict bus load results while enhancing robustness for holiday predictions,making it better adapted to real-world prediction scenarios.

线上中文学习平台Lingo Bus和Lingo Ace比较研究

Lingo Bus和Lingo Ace平台是当前受到市场青睐的知名线上中文学习平台。对两个学习平台的建设、教学和管理营销三个方面的情况进行比较研究后发现:两个平台均通过线上直播课程面向海外青少儿教授中文,均建立了各自的官网和客户端,在品牌定位、课程资源体系、选课方式和学习者服务模式等方面的设计上都有差异,针对教师选拔、培训的侧重点和严格程度也有不同的标准;两个平台均注重通过口碑、新闻软文和社交媒体等途径进行营销,但在推广方式和营销经费投入力度方面做法不同。线上中文学习平台应建设本土化和标准化教学资源,提升系统稳定性和智能化水平,完善教师管理机制,建立良好服务体系,组建本土团队,实施精准营销等发展策略。

Factors Influence Hanoians’ Choice of Non-Motorized Transport Mode to Access Bus Stations

Hanoi’s rapid urbanization has led to a surge in private vehicle ownership, particularly motorcycles, amidst inadequate public transportation infrastructure. Despite government efforts, many still prefer motorized transport, citing mobility and safety concerns, exacerbated by insufficient pedestrian infrastructure. This study examines the motivations behind this reliance on motorized vehicles, particularly motorcycles, in Hanoi. Findings reveal safety and convenience as primary factors driving motorized transport use, especially for accessing bus stations. Economic incentives could promote non-motorized travel and public transport adoption. Policy implications highlight the importance of addressing economic factors and improving access infrastructure to manage motorized vehicle reliance and foster sustainable urban mobility in Hanoi.

Charging Ahead with E-Buses: Benefits, Costs, and Transition Roadmap

This paper reaches a recommendation for the 10-year e-bus transition roadmap for New York City. The lifecycle model of emission reduction demonstrates the ecological and financial impacts of a complete transition from the current diesel bus fleet to an all-electric bus fleet in New York City by 2033. This study focuses on the NOx pollution, which is the highest among all major cities by Environmental Protection Agency (EPA) and greenhouse gases (GHG) with annual emissions of over five million tons. Our model predicts that switching to an all-electric bus fleet will cut GHG emissions by over 390,000 tons and NOx emissions by over 1300 tons annually, in addition to other pollutants such as VOCs and PM 2.5. yielding an annual economic benefit of over 75.94 million USD. This aligns with the city mayor office’s initiative of achieving total carbon neutrality. We further model an optimized transition roadmap that balances ecological and long-term benefits against the costs of the transition, emphasizing feasibility and alignment with the natural replacement cycle of existing buses, ensuring a steady budgeting pattern to minimize interruptions and resistance. Finally, we advocate for collaboration between government agencies, public transportation authorities, and private sectors, including electric buses and charging facility manufacturers, which is essential for fostering innovation and reducing the costs associated with the transition to e-buses.

Construction and realization of the knowledge base and inference engine of an IDSS model for air-conditioning cooling/heating sources selection

The knowledge representation mode and inference control strategy were analyzed according to the specialties of air-conditioning cooling/heating sources selection. The constructing idea and working procedure for knowledge base and inference engine were proposed while the realization technique of the C language was discussed. An intelligent decision support system (IDSS) model based on such knowledge representation and inference mechanism was developed by domain engineers. The model was verified to have a small kernel and powerful capability in list processing and data driving, which was successfully used in the design of a cooling/heating sources system for a large-sized office building.

Application of water loop variable refrigerant flow air-conditioning system in large-scale buildings in northern China

A water loop variable refrigerant flow（WLVRF）air-conditioning system is designed to be applied in large-scale buildings in northern China.The system is energy saving and it is an integrated system consisting of a variable refrigerant flow（VRF）air-conditioning unit,a water loop and an air source heat pump.The water loop transports energy among different regions in the buildings instead of refrigerant pipes,decreasing the scale of the VRF air-conditioning unit and improving the performance.Previous models for refrigerants and building loads are cited in this investigation.Mathematical models of major equipment and other elements of the system are established using the lumped parameter method based on the DATAFIT software and the MATLAB software.The performance of the WLVRF system is simulated.The initial investments and the running costs are calculated based on the results of market research.Finally,a contrast is carried out between the WLVRF system and the traditional VRF system.The results show that the WLVRF system has a better working condition and lower running costs than the traditional VRF system.

Entropy Assessment on Environmental Influence of Condense Heat in Recovery System in Air-Conditioning Refrigerating Machine

This paper presented an entropy evaluation method for the influences of condense heat recovery system on the environment.Aiming at the damage of the condense heat to the environment,an entropy of resource loss and an emission entropy from the condense heat recovery system in the air conditioning refrigerating machine were introduced.For the evaluation of the entropies,we developed a new algorithm for the parameter identification,called the composite influence coefficient,based on the Least Squares Support Vector Machine method.By simulation,the numerical experiments shows that the Least Squares Support Vector Machine method is one of the powerful methods for the parameter identification to compute the damage entropy of the condense heat,with the largest training error being-0.025(the relative error being-3.56%),and the biggest test error being 0.015(the relative error being 2.5%).

Impact of summer office set air-conditioning temperature on energy consumption and thermal comfort

To explore the relationship between summer office set air-conditioning temperature and energy consumption related to air conditioning use to provide human thermal comfort,a comparison experiment was conducted in three similar offices at temperatures of 24,26 and 28 ℃ respectively. A thermal comfort questionnaire survey was conducted. It is demonstrated that air-conditioner energy consumption at the set temperature of 28 ℃ is 113% and 271% lower than at 26 ℃ and 24 ℃,respectively. A linear relationship exists between air-conditioner energy consumption and the indoor and outdoor temperature difference. When comfortably dressed,over 80% of research participants accept the set temperature of 28 ℃. The regression analysis leads to a neutral temperature of 26.2 ℃ and an acceptable temperature of 28.2 ℃ for over 80% of the research participants subjects,indicating that the current 26 ℃ set temperature for offices in summer,required by Chinese General Office of the State Council,can be increased to 28 ℃. Moreover,analysis of predicted mean vote(PMV) index shows that a set temperature of 27 ℃,not 26 ℃,is sufficiently comfortable for office staff wearing long-sleeve shirts,long pants and leather shoes.

Genetic Optimization Algorithm of PID Decoupling Control for VAV Air-Conditioning System

Variable-air-volume (VAV) air-conditioning system is a multi-variable system and has multi coupling control loops. While all of the control loops are working together, they interfere and influence each other. A multivariable decoupling PID controller is designed for VAV air-conditioning system. Diagonal matrix decoupling method is employed to eliminate the coupling between the loop of supply air temperature and that of thermal-space air temperature. The PID controller parameters are optimized by means of an improved genetic algorithm in floating point representations to obtain better performance. The population in the improved genetic algorithm mutates before crossover, which is helpful for the convergence. Additionally the micro mutation algorithm is proposed and applied to improve the convergence during the later evolution. To search the best parameters, the optimized parameters ranges should be amplified 10 times the initial ideal parameters. The simulation and experiment results show that the decoupling control system is effective and feasible. The method can overcome the strong coupling feature of the system and has shorter governing time and less over-shoot than non-optimization PID control.

A fully distributed robust optimal control approach for air-conditioning systems considering uncertainties of communication link in IoT-enabled building automation systems

Internet of Things(IoT)technologies are increasingly implemented in buildings as the cost-effective smart sens-ing infrastructure of building automation systems(BASs).They are also dispersed computing resources for novel distributed optimal control approaches.However,wireless communication networks are critical to fulfill these tasks with the performance influenced by inherent uncertainties in networks,e.g.,unpredictable occurrence of link failures.Centralized and hierarchical distributed approaches are vulnerable against link failure,while the robustness of fully distributed approaches depends on the algorithms adopted.This study therefore proposes a fully distributed robust optimal control approach for air-conditioning systems considering uncertainties of com-munication link in IoT-enabled BASs.The distributed algorithm is adopted that agents know their out-neighbors only.Agents directly coordinate with the connected neighbors for global optimization.Tests are conducted to test and validate the proposed approach by comparing with existing approaches,i.e.,the centralized,the hierarchical distributed and the fully distributed approaches.Results show that different approaches are vulnerable against to uncertainties of communication link to different extents.The proposed approach always guarantees the optimal control performance under normal conditions and conditions with link failures,verifying its high robustness.It also has low computation complexity and high optimization efficiency,thus applicable on IoT-enabled BASs.

Selection of Weather Parameters for Air-Conditioning System Design for Buildings with Long Thermal Lag

Two building factors-a longer thermal lag of more than one hour for building envelops and a lag of indoor radiation to convert into cooling load-have impact on the instantaneous heat input and instantaneous cooling load.So the two factors should be taken into account when selecting the weather parameters for air-conditioning system design.This paper developed a new statistic method for the rational selection of coincident solar irradiance,dry-bulb and wet-bulb temperatures.The method was applied to historic weather records of 25 years in Hong Kong to generate coincident design weather data.And the results show that traditional design solar irradiance,dry-bulb and wet-bulb temperatures may be significantly overestimated in many conditions,and the design weather data for the three different constructions is not kept constant.

The Experiment and Simulation of Solid Desiccant Dehumidification for Air-Conditioning System in a Tropical Humid Climate

The aim of this research was to study and design a solid desiccant dehumidification system suitable for tropical climate to reduce the latent load of air-conditioning system and improve the thermal comfort. Different dehumidifiers such as desiccant column and desiccant wheel were investigated. The ANSYS and TRASYS software were used to predict the results of dehumidifiers and the desiccant cooling systems, respectively. The desiccant bed contained approximately 15 kg of silica-gel, with 3 mm average diameter. Results indicated that the pressure drop and the adsorption rate of desiccant column are usually higher than those of the desiccant wheel. The feasible and practical adsorption rate of desiccant wheel was 0.102 kgw/h at air flow rate 1.0 kg/min, regenerated air temperature of 55?C and at a wheel speed of 2.5 rpm. The humidity ratio of conditioning space and cooling load of split-type air conditioner was decreased to 0.002 kgw/kgda (14%) and 0.71 kWth (19.26%), respectively. Consequently, the thermal comfort was improved from 0.5 PMV (10.12% PPD) to 0.3 PMV (7.04% PPD).

An Energy-Saving Control Strategy on Central Air-Conditioning System

An energy-saving control strategy based on predictive control for central air-conditioning systems is proposed in this paper. The cold load model is developed to describe the dynamic characteristics of temperature control systems, and then parameters in the cold load model and in the central air-conditioning system model are estimated. Generalized predictive control (GPC) is used to establish an optimization model to minimize the consumption of energy and the control error of temperature. The simulated annealing (SA) algorithm, combined with quadratic programming, is adopted to solve the optimal problem. Contrasted with the simulation of traditional PID control, the results prove the effectiveness of this proposed strategy.

Application of Fuzzy Comprehensive Evaluation to Air-conditioning Competitive Power Analysis

As the conceptual design of air-conditioning is done using the theory of Quality Function Deployment (QFD),cus- tomer requirements should be understood and the product competitive power be analyzed as exactly as possible for new product de- signing.Lots of information in the process of this research is fuzzy and uncertain,but traditional QFD can not deal with it well. Fuzzy theory can solve the problem.So a fuzzy model for analyzing product competitive power is formulated in this paper to im- prove traditional QFD,after that it is applied to analyze air-conditioning competitive power.When air-conditioning competitive power is analyzed using this model,firstly the importance weight of the customer requirements o fair-conditioning is determined us- ing the Analytic Hierarchy Process (AHP) weighting process,then air-conditloning competitive power is evaluated using fuzzy comprehensive evaluation.It is proved that the model is feasible and has good applicability.

Application of Dual Throttling Air-Conditioning System to Explosion-Proof Frequency Converter

An explosion-proof dual throttling air-conditioning system was put forward to solve the heat dissipation and internal dewing problems of explosion-proof frequency converter in the underground coal mine. This study investigated the feasibility and benefits of explosion-proof dual throttling cooling and dehumidification air-conditioning system applied to the explosion-proof frequency converter. The physical model of dual throttling air-conditioning system was established and its performance parameter was described by mathematical method. The design calculation of the system has also been done. The experimental result showed that the system reached the steady state at the refrigeration mode after running 45 min, and the maximum internal temperature of the flame-proof cavity was 31.0 ℃. The system reached the steady state at the dehumidification mode after running 37 min. The maximum internal relative humidity and temperature of the flame-proof cavity were 33.4% and 36.3 ℃, respectively. Therefore, the proposed system had excellent ability of heat dissipation and avoided internal dewing. Compared with water cooling system, it was more energy-saving and economical. The airflow field of dual throttling air-conditioning system was also studied by CFD simulation. It was found that the result of CFD numerical simulation was highly consistent with the experimental data.

Simulation of Artificial Intelligence for Automotive Air-conditioning System

The artificial intelligence is applied to the simulation of the automotive air-conditioning system ( AACS )According to the system's characteristics a model of AACS, based on neural network, is developed. Different control methods of AACS are discussed through simulation based on this model. The result shows that the neural- fuzzy control is the best one compared with the on-off control and conventional fuzzy control method.It can make the compartment's temperature descend rapidly to the designed temperature and the fluctuation is small.

Energy performance assessment on central air-conditioning system of commercial building: A case study in China

Energy performance assessment on central air-conditioning system is essential to optimize operating, reduce operating costs, improve indoor environmental quality, and determine whether the retrofitting of the equipment is necessary. But it is difficult to evaluate it reasonably and comprehensively due to its complexity. A "holistic" approach was discussed to evaluate the energy performance of central air-conditioning system for an extra-large commercial building in a subtropical city. All procedures were described in detail, including field investigation method, field measurement instruments, data processing and data analyzing. The main factors affecting energy consumption of air-conditioning system were analyzed and the annual cooling-energy use intensity of this building was calculated and also compared with other shopping malls and other types of buildings in Guangzhou. And COP(coefficient of performance) of chiller, water transfer factor of chilled water system and cooling water system were taken into consideration. At last, the thermal comfort and indoor air quality issues were addressed. The results show that the chilled water pumps are over-sized and the indoor environmental quality should be improved. The purpose of this work is to provide reference for energy performance assessment method for air-conditioning system.

Point Cloud Based Semantic Segmentation Method for Unmanned Shuttle Bus

The complexity of application scenarios and the enormous volume of point cloud data make it difficult to quickly and effectively segment the scenario only based on the point cloud.In this paper,to address the semantic segmentation for safety driving of unmanned shuttle buses,an accurate and effective point cloud-based semantic segmentation method is proposed for specified scenarios(such as campus).Firstly,we analyze the characteristic of the shuttle bus scenarios and propose to use ROI selection to reduce the total points in computation,and then propose an improved semantic segmentation model based on Cylinder3D,which improves mean Intersection over Union(mIoU)by 1.3%over the original model on SemanticKITTI data;then,a semantic category division method is proposed for road scenario of shuttle bus and practical application requirements,and then we further simplify the model to improve the efficiency without losing the accuracy.Finally,the nuScenes dataset and the real gathered campus scene data are used to validate and analyze the proposed method.The experimental results on the nuScenes dataset and our data demonstrate that the proposed method performs better than other point cloud semantic segmentation methods in terms of application requirements for unmanned shuttle buses.Which has a higher accuracy(82.73%in mIoU)and a higher computational efficiency(inference speed of 90 ms).

A novel intrusion detection model for the CAN bus packet of in-vehicle network based on attention mechanism and autoencoder

The attacks on in-vehicle Controller Area Network(CAN)bus messages severely disrupt normal communication between vehicles.Therefore,researches on intrusion detection models for CAN have positive business value for vehicle security,and the intrusion detection technology for CAN bus messages can effectively protect the invehicle network from unlawful attacks.Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings.Hence,to address the shortcomings of the previous machine learning-based intrusion detection technique,we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection(AMAEID).The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input.Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level.Finally,the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not.The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms,demonstrating the effectiveness of the AMAEID model.

Research on the Arrangement of Dew Point Temperature Detectors of Capillary Plane Radiation Air-Conditioning

Based on analysis of the reason and process of condensation on ceiling radiant cooling panels, two kinds of arrangement of detectors are put forward. The physical model is established, the results show that detectors are arranged as the form of triangle is more suitable. It can not only satisfy the use requirement but also it is economical and practical. Finally we can conclude that the inlet water temperature 0.5°C higher than dew point temperature is safe and reliable.