Indoor localization systems are crucial in addressing the limitations of traditional global positioning system(GPS)in indoor environments due to signal attenuation *** complex indoor spaces become more sophisticated,i...
详细信息
Indoor localization systems are crucial in addressing the limitations of traditional global positioning system(GPS)in indoor environments due to signal attenuation *** complex indoor spaces become more sophisticated,indoor localization systems become essential for improving user experience,safety,and operational *** localization methods based on Wi-Fi fingerprints require a high-density location fingerprint database,but this can increase the computational burden in the online *** networks,which integrate prior knowledge or domain expertise,are an effective solution for accurately determining indoor user *** networks use probabilistic reasoning to model relationships among various localization parameters for indoor environments that are challenging to *** article proposes an adaptive Bayesian model for multi-floor environments based on fingerprinting techniques to minimize errors in estimating user *** proposed system is an off-the-shelf solution that uses existing Wi-Fi infrastructures to estimate user’s *** operates in both online and offline *** the offline phase,a mobile device with Wi-Fi capability collects radio signals,while in the online phase,generating samples using Gibbs sampling based on the proposed Bayesian model and radio map to predict user’s *** results unequivocally showcase the superior performance of the proposed model when compared to other existing models and *** proposed model achieved an impressive lower average localization error,surpassing the accuracy of competing ***,this noteworthy achievement was attained with minimal reliance on reference points,underscoring the efficiency and efficacy of the proposed model in accurately estimating user locations in indoor environments.
To predict the lithium-ion(Li-ion)battery degradation trajectory in the early phase,arranging the maintenance of battery energy storage systems is of great ***,under different operation conditions,Li-ion batteries pre...
详细信息
To predict the lithium-ion(Li-ion)battery degradation trajectory in the early phase,arranging the maintenance of battery energy storage systems is of great ***,under different operation conditions,Li-ion batteries present distinct degradation patterns,and it is challenging to capture negligible capacity fade in early *** the data-driven method showing promising performance,insufficient data is still a big issue since the ageing experiments on the batteries are too slow and *** this study,we proposed twin autoencoders integrated into a two-stage method to predict the early cycles'degradation *** two-stage method can properly predict the degradation from course to *** twin autoencoders serve as a feature extractor and a synthetic data generator,***,a learning procedure based on the long-short term memory(LSTM)network is designed to hybridize the learning process between the real and synthetic *** performance of the proposed method is verified on three datasets,and the experimental results show that the proposed method can achieve accurate predictions compared to its competitors.
Smart cities, industrial automation, healthcare, and environmental monitoring are just a few of the industries that have seen revolutionary changes as a result of Wireless Sensor Networks’ (WSNs) explosive growth. WS...
详细信息
ISBN:
(纸本)9783031782756
Smart cities, industrial automation, healthcare, and environmental monitoring are just a few of the industries that have seen revolutionary changes as a result of Wireless Sensor Networks’ (WSNs) explosive growth. WSNs are significantly hampered by the limited energy resources of their sensor nodes, which are usually battery-powered and placed in inaccessible locations, despite their wide-ranging applications. As a result, energy efficiency is now a crucial component of these networks’ operation and design. Though these protocols frequently fail to adjust to the dynamic and unpredictable nature of WSNs, traditional energy-aware routing methods have been created to decrease energy consumption by choosing the best paths for data transfer. By allowing sensor nodes to learn from their surroundings and make wise routing decisions, the machine learning field of reinforcement learning (RL) provides a viable answer to these problems. In contrast to conventional techniques, RL-based protocols provide continuous energy optimization by dynamically modifying their routing strategies in response to real-time feedback. This paper investigates how to include RL methods—specifically, Q-learning and SARSA—into WSN energy-aware routing protocols. The suggested method creates a more distributed and scalable solution by enabling each node to independently learn and modify its routing choices. The effectiveness of RL-based routing protocols is compared to traditional methods through comprehensive simulations. The findings show that by slowing down the rate at which energy is being used up by each node, RL not only increases energy efficiency but also lengthens the network's operational life. In particular, Q-learning demonstrates a notable improvement in sustaining data delivery rates and network connectivity under various circumstances. Although a little more computationally demanding, the SARSA algorithm offers greater flexibility in situations where network topology changes often. Th
In this paper, we consider a degree sum condition sufficient to imply the existence of k vertex-disjoint chorded cycles in a graph G. Let σ4(G) be the minimum degree sum of four independent vertices of G. We prove th...
详细信息
This letter presents a 60-GHz analog phase-locked loop (PLL) incorporating a half-wavelength standing-wave oscillator (SWO) as part of the clock distribution network in a sub-THz 2-D phased-array transceiver. The freq...
详细信息
In this work we utilize topology optimization to design and simulate an etching pattern for a layered diamond microdisk for efficient coupling from a nitrogen vacancy center emitter to free space. Other methods of cou...
详细信息
In recent years, the increasing popularity of the Internet and its applications has led to significant growth in network users. Subsequently, the number and complexity of cyber-attacks realized against home users, bus...
详细信息
This elaboration presents the synthesis of the Takagi-Sugeno type Fuzzy Logic controller realizing the programmable parameters of the state feedback controller together with the steady state current for the active mag...
详细信息
Enabling the integration of distributed energy resources (DERs) into the wholesale market, as prompted by the FERC Order 2222, introduces substantial operational complexities. To align with the current wholesale energ...
详细信息
Skeleton-based video anomaly detection (SVAD) is a crucial task in computer vision. Accurately identifying abnormal patterns or events enables operators to promptly de-tect suspicious activities, thereby enhancing saf...
详细信息
暂无评论