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This research focuses on developing a neural network model in the Python programming language to solve the technological problem of forecasting potato yields with limited agroclimatic data. The developed program is consi...

Abstract Fine particulate matter produced during the rapid industrialization over the past decades can cause significant harm to human health. Twin-fluid atomization technology is an effective means of controlling fine p...

IntroductionEarly and accurate diagnosis of skin cancer has a huge impact on the survival rate of patients and deep learning-based CNN and dermatologists' intelligence support can fasten the diagnosis not only within the...

Abstract Advances in AI have transformed the traditional Internet of Things (IoT) into smarter, more versatile next-generation devices. Enhanced connectivity among sensors, actuators, and appliances boosts data availabil...

Digital Twin Networks (DTNs) are emerging as a key enabler for the robust optimization and lifecycle management of next-generation networks. However, current DTN approaches still rely heavily on manual design, implementa...

Nowadays, performing multi-objective optimizations of actual building designs is one of the most challenging problems of the building energy efficiency area. This paper aims to propose an efficient method to solve multi-...

Optimal evacuation route planning is a crucial factor in disaster mitigation, especially in areas with limited communication infrastructure. This study proposes the application of the A-Star method for evacuation route o...

By introducing the artificial intelligence technology, on improved Nelder-Mead acceleration algorithm based on the neural network is proposed to obtain better optimization results. A back analysis method for construction...

Abstract The current study employs Bayesian-regularization optimizer technique with artificial neural networks (BROT-ANNs) to investigate the significance of local thermal non-equilibrium influences on wax + sand-bas...

A high efficiency hardware integration of neural networks benefits from realizing nonlinearity, network connectivity and learning fully in a physical substrate. Multiple systems have recently implemented some or all of t...

Abstract Carbon markets play a critical role in emission reduction and sustainable economic transition; however, carbon price series exhibit high volatility, nonlinear dynamics, and complex cross-feature interactions, ma...

Wireless Sensor Networks (WSNs) are extensively used in applications such as environmental monitoring, surveillance, and smart security, but their performance is limited by the restricted energy capacity of sensor nodes,...

Abstract To address the challenge of low adaptability in distribution network planning caused by significant regional differences in electricity consumption, this paper proposes a distribution network planning method bas...

Abstract Background Protein-protein interaction (PPI) network-based protein function prediction algorithms, which use the guilt-by-association principle, are widely applied in medical and human domains, but they are comp...

Abstract While multi-access edge computing (MEC) enables flexible task offloading, the inherent dynamism and complexity of real-world environments, accompanied by various uncertainties, exacerbate the challenges in offlo...

BackgroundThe thermal diffusivity and vertical seepage velocity of porous media are critical to characterizing the mechanisms underlying subsurface heat transfer. These two parameters are typically determined through inv...

The long wavelength infrared (LWIR) range (8–14 µm) is crucial for thermal radiation detection, necessitating effective camouflage against advanced infrared technologies. Conventional camouflage approaches often rel...

This paper investigates secure and energy-efficient multi-user symbiotic radio (SR) communication assisted by an active reconfigurable intelligent surface (ARIS). We consider a downlink multi-user unicast scenario where ...

Abstract Inventory management is a core part of supply chains, and over the years it has been increasingly challenged by the need to balance economic performance with environmental considerations. While prior reinforceme...

Silicon photonics enables compact integrated photonic devices with versatile functionalities and mass manufacturing capability. However, the optimization of high-performance free-form optical devices is still challenging...

This paper addresses the challenge of packet-based information routing in large-scale communication networks. The problem is framed as a constrained statistical learning task, where each network node operates using only ...

Abstract In this work, we investigated the path loss (PL) profile of the outdoor radio channel in the 800 MHz band for the Icaraí region in the city of Niterói. This frequency band has recently been reserved by the bra...

The main objectives of this study are to enhance the power extraction of photovoltaic (PV) systems under rapidly changing ecological circumstances using Maximum Power Point Tracking (MPPT) and to improve the power qualit...

Abstract Accurate and real-time prediction of lost circulation is essential for ensuring drilling safety and operational efficiency. Existing data-driven approaches, however, often lack effective integration of domain ex...