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Frequent fire incidents on electric bicycles; have brought great harm to consumers’ personal and property safety. This article sort and analyze the data, combine the collected accident reports of electric bicycles. Due to the incompleteness of the data, this article use Bayesian Network to construct the Bayesian network topology model of electric b...
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... prior probabilities of the obtained evidence nodes and the conditional probabilities of the four nodes judged by the experts are input into the Bayesian network. The fire risk of the vehicle was reasoned through Bayesian network, and the fire risk of the product was calculated to be 1.44%, as shown in Fig 1. The risk level of this product is low, in accordance with the classification principle in Table 2. Assume that a fire event has occurred in the product. ...
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The fresh cold chain network is complex, and the interruption risk can significantly impact it. Based on the Bayesian theory, we constructed a fresh cold chain network interruption risk topology structure. The probability of each root node was predicted and calculated based on the fuzzy set theory. The evaluation model was then validated and improv...
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... Among traditional risk analysis methods, the Bayesian network (BN) is an effective causal analysis tool for uncertain knowledge in probabilistic systems [6]. As an analytical tool, BN can be combined with other analytical methods (bow-tie method, fault tree method, fuzzy theory, etc.), which can be used to perform risk analysis under conditions of imperfect historical data and make the assessment more effective in accident analysis [7][8][9]. Therefore, the BN model is widely used for risk analysis in various fields. Fuzzy logic was incorporated into the BN used for the safety assessment of oil and gas pipelines, and the most significant causes of oil and gas pipeline failures were found [10]. ...
... Very Given the variations in expertise across different domains, the two critical influencing factors of expertise disparities, namely, 'education' and 'years of experience', were selected [9,16,25]. Table 4 presents the expert scoring weights. The experts' opinions are processed accordingly using Formula (4). ...
There is a lack of a quantitative assessment of the risk factors associated with poisoning and asphyxiation accidents in steel enterprises, especially the insufficient treatment of uncertainty in risk analysis. To address this issue, this work proposed a risk assessment method based on fuzzy Bayesian network (FBN), which established a risk assessment indicator system for poisoning and asphyxiation from four aspects, including human, material, environmental, and management factors, and illustrated the relationship between these risk factors through fault tree analysis (FTA). Taking a steel plant in China as an example, fuzzy set theory (FST) and expert surveys were combined to determine the prior probabilities and conditional probabilities of Bayesian network (BN) nodes. The results show that (i) the probability of poisoning and asphyxiation accidents in this steel plant is 74%; (ii) among the various influencing factors, defective or inadequate monitoring and alarm devices, isolation devices, equipment inspection systems, and toxic gas operation management are identified as the critical contributors; and (iii) this accident probability has decreased to 47% after rectification measures and reassessment. The findings of this research offer valuable insights for steel enterprises in preventing poisoning and asphyxiation accidents.
... The pulling capacity of the cycle can be enhanced by increasing the battery capacity which would add additional cost based on capacity. The decrease of air contamination should be possible by advancing the utilization of electric bicycles [6][7][8]. An electric bike also known as an eco-accommodating bi-cycle assimilated with electrically powered appliance is mainly preferred. ...
In the recent days, carbon emission from the vehicles are found to increase the level of air pollution in a huge manner. In order to reduce the pollution due to transportation, electric vehicles are seen as an alternative. This approach paved way for developing an electric bicycle by incorporating 250 W BLDC hub motor, 295.6 WH lithium-ion battery and pedal assist system (PAS). The maximum speed of the bicycle is 25 km/h. The distance covered using PAS is 75 km. The maximum carrying capacity is 120 kg with a charging time of 2.5 to 3 hours. The pedal assisting system helps to share the torque between manual pedalling & electric motoring. This ensures that the battery is used in an efficient manner. The cost of this bicycle includes cycle assembly, battery, hub motor, controller circuit and wireless odometer. The total expenses involved in developing this prototype is nearly 38.57% lesser without profit when compared to other products available in the market. The pulling capacity of the cycle can be enhanced by increasing the battery capacity which would add additional cost based on capacity.
The development in the field of electrical energy has been growing increasingly due to the need of this energy in daily life. The reliability and safety of electrical power systems and equipment represent complex problems that are difficult to solve by conventional methods such as Fuzzy Logic and Artificial Neural Networks. Bayesian network is recently used to overcome some limitations in the conventional methods. This paper represents a bibliographic review about the use of Bayesian networks in the field of electric systems. This paper seeks to answer the following questions: (i) What are the areas of interest? (ii) What are the most active countries in this field?? (iii) Who are the most participating authors in this field? (iv) which year witnesses the largest number of publications? (v) What is the most widespread field related to this research? (vi) What is the most used system in terms of application? This field witnesses a slight increase in the number of publications in the last two decades (1999–2021), with a note of sharp increase in publishing in the last two years. It is observed that reliability assessment and fault diagnosis are the most common fields. Furthermore, it is found that China and USA are the highest active countries in this topic. Electric Power and Energy Systems Journal and IEEE Transactions on Power Systems Journal are the lead source documents, and most of the documents used electric power systems as an application. This paper will help researchers to know the versability features of BN and to identify the gaps in the use of BN in electric domains.
