The Energy Storage System (ESS) is an important component of the Electric Vehicle (EV) system, wherein Lithium-ion (Li-ion) batteries are commonly deployed owing to high energy storage capacity and durability. But charging and discharging over time causes reduction in the efficiency of batteries. Further, degradation becomes very fast when batteries reach End of Life (EOL). This implies the need for efficient battery management systems in EVs. The Battery Management System (BMS) monitors various indicators of the battery including State of Charge (SOC), Remaining Useful Life (RUL), and State of Health (SOH). The monitoring of RUL and SOH is especially useful for forecasting the degradation of batteries and thus minimizing maintenance expenses. In this work, a deep learning framework-based approach for predicting the RUL and SOH of Li-ion batteries has been presented. In the initial stage, the acquired health data from the batteries is preprocessed using Min-Max normalization for consistency in data. After that, the prediction process is done using the developed Dream Optimized Explainable Bayesian Gated Recurrent Unit (DO EB_GRU). In this method, the Explainable Bayesian Gated Recurrent Unit (EB_GRU) is optimized using the Dream Optimization Algorithm (DOA). Experimental examination specified that DO EB_GRU accomplished an MSE of 0.0016, MAE of 0.015, R-Squared of 0.956.
Priya A Geevarghese, L. Suresh, Aneesh P. Thankachan· International Conference on...· 0 citations
Traffic signs are road facilities that communicate, direct, limit, caution or teach information, whether in the form of words or symbols. As the demand for the intelligence of vehicles is on the rise, there is a great need to invent and identify traffic signs automatically using technology. Nonetheless, the identification of traffic signs is not that easy, as a number of negative parameters exist, such as bad weather, change of perspective, physical impairment, and others. Currently, most of the available text mining algorithms help in processing the whole data to identify the traffic sign images. In this proposed research, an extensive sign board detection algorithm is developed where AlexNet image classification algorithm forms the premier stage. It is mainly focussed on the process of detection with the improvement of the traffic signs using a boundary enhancement algorithm along with the average filter. This helps in reducing the noise and enhances the sign to be fed into the classifier system. This approach enhances precision of 99.27%, sensitivity of 99.41% and specificity of 99.47%. Thus the proposed algorithm minimizes the time taken to detect the traffic sign in misty weather.
ASHWINI A, G. Santhiya, L. Suresh et al.· International Conference on...· 0 citations
Mobile Ad-hoc Networks (MANETs) are a useful means for communication in military and emergency situations, as well as for various types of smart sensors and other mobile applications, since they allow mobile nodes to interact with each other without relying on a fixed communication structure. However, fast-moving and unpredictable nodes result in frequent changes to the topology of the network which also result in inconsistent route selections and more energy used to send and receive packets, thus leading to lower overall performance on the network. This paper introduces an adaptive routing scheme based on the Shrike Optimization Algorithm (ShOA) for improving MANET performance by overcoming these issues. The proposed Scheme identifies the most efficient routing paths through the use of the predation and decision-making abilities of Shrike Birds. This Shrike-based routing design reduces the amount of information lost in the form of packet losses and routing overheads, while providing reliable transfers of data by properly balancing the trade-off between exploring and exploiting. Based on extensive simulation results, the proposed ShOA-based MANET exhibits substantially improved performance in the areas of packet delivery ratios, end-to-end delay, throughput, and overall durabilitys compared to both optimization techniques currently used and conventional routing protocols. Therefore,the results support the conclusion that the Shrike Optimization Algorithm offers aviable option for developing reliable and energy-efficient mobile ad - hoc networks for communication
V. Vishu, S. Sivagnanam, L. Suresh et al.· International Conference on...· 0 citations
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