EFLOP: a sparsity-aware metric for evaluating computational cost in spiking and non-spiking neural networks by Simon Narduzzi, Friedemann Zenke, Shih-Chii Liu, L Andrea Dunbar

“…However, existing computational frameworks fail to accurately estimate the cost of running sparse networks on modern time-stepped hardware, which exploits sparsity by skipping zero-valued operations. …”
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Routing algorithm for heterogeneous computing force requests based on computing first network by ZHANG Gang, LI Xi

“…The experiment verifies that algorithm has been optimized by an average of 8.85%, 15.51%, and 17.03% in terms of transmission success rate, convergence delay ratio, and load balancing compared to the IGAGCT algorithm and RBDQN algorithm, and 10.41%, 16.5%, and 16.81%, respectively from three aspects: heterogeneous request success rate, algorithms convergence delay rate, and load error rate of computing first networks.…”
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Design of Periodic Neural Networks for Computational Investigations of Nonlinear Hepatitis C Virus Model Under Boozing by Abdul Mannan, Jamshaid Ul Rahman, Quaid Iqbal, Rubiqa Zulfiqar

“…We employ periodic neural networks, optimized using a hybrid genetic algorithm and the interior-point algorithm, to solve a system of six coupled nonlinear differential equations representing hepatitis C virus dynamics. …”
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Network-based malcode detection technology by WU Bing1, YUN Xiao-chun2, GAO Qi1

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Optimizing Battery Charging in Wireless Sensor Networks: Performance Assessment of MPPT Algorithms in Different Environmental Settings by Abdullah Fadhil Noor Shubbar, Serkan Savaş, Osman Güler

“…Given the critical role of battery performance in WSN reliability, efficient energy management through Maximum Power Point Tracking (MPPT) algorithms is essential to adapt to variable environmental conditions such as solar irradiance and ambient temperature.Objective: This study aims to comparatively assess the performance of four widely adopted MPPT algorithms-Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic (FL), and Particle Swarm Optimization (PSO)-in enhancing battery charging efficiency in PV-powered WSNs under dynamic environmental conditions.Methods: A simulation-based evaluation framework was developed using MATLAB/Simulink to model a PV-powered WSN system. …”
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Multi‐objective multi‐period optimal site and size of distributed generation along with network reconfiguration by Ghulam Abbas, Zhi Wu, Aamir Ali

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Optimizing FCN for devices with limited resources using quantization and sparsity enhancement by Muhammad Faizan-Khan, Nisar Ali, Raja Hashim Ali, Areej Alasiry, Mehrez Marzougui, Shabbab Ali Algamdi, Yunyoung Nam

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Queuing Delay Reduction based on Network Traffic Patterns: A Predictive QoS Framework For Point-To-Point Communications by Espinal Albert, Sanchez Padilla V.

“…Ensuring optimal quality of service (QoS) in computer networks requires a detailed assessment of performance metrics, with data network queuing delay within intermediate devices being critical parameters. …”
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Quantum PSO-Based Optimization of Secured IRS-Assisted Wireless-Powered IoT Networks by Abid Afridi, Iqra Hameed, Insoo Koo

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GNN-based optimization algorithm for joint user scheduling and beamforming by Shiwen HE, Jun YUAN, Zhenyu AN, Min ZHANG, Yongming HUANG, Yaoxue ZHANG

“…The coordinated multi-point (CoMP) transmission technology has the characteristics of reducing co-channel interference and improving spectral efficiency.For the CoMP technology, user scheduling (US) and beamforming (BF) design are two fundamental research problems located in the media access control layer and the physical layer, respectively.Under the consideration of user service quality requirements, the joint user US-BF optimization problem was investigated with the goal of maximizing network throughput.To overcome the problem that the traditional optimization algorithm had high computational cost and couldn’t effectively utilize the network historical data information, a joint US and power allocation (M-JEEPON) model based on graph neural network was proposed to realize joint US-BF optimization by combining the beam vector analytical solution.The simulation results show that the proposed algorithm can achieve the performance matching or even better than traditional optimization algorithms with lower computational overhead.…”
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An intelligent environmental-sensorless model for real-time optimization in photovoltaic-energy systems: Fast computation, long-term performance, and experimental validation by Ambe Harrison, Hassan M. Hussein Farh, Abdullrahman A. Al-Shamma'a, Saad Mekhilef

“…Accurate determination of the Maximum Power Point (MPP) is critical for optimizing photovoltaic (PV) systems, especially in resource-constrained settings where the use of climatic sensors is impractical or cost-prohibitive. …”
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A point cloud segmentation network with hybrid convolution and differential channels by Xiaoyan Zhang, Yantao Bu

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Optimized Offloading in Vehicular Edge Computing: A Game Theoretic Analysis by Abdelkarim Ait Temghart, Mbarek Marwan, Mohamed Baslam

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Mod Tanh‐Activated Physical Neural Network MPPT Control Algorithm for Varying Irradiance Conditions by Khuong Nguyen‐Vinh, Surender Rangaraju, Michal Jasinski

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Applying Optimized ANN Models to Estimate Dew Point Pressure of Gas Condensates by Luo Han, Saeed Sarvazizi

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TFNet: point cloud Semantic Segmentation Network based on Triple feature extraction by Yong Li, Falin Chen, Qi Lin, Zhen Li, Dongxu Gao, Jingchao Yang

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An innovative coverage optimization method for smart information monitoring in agricultural IoT using the multi-strategy Pelican optimization algorithm by Wei Chen, Qike Cao, Bingyu Cao, Bo Jin

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Coded Caching: User to Access Points Distribution in Wireless Local Area Networks by Mirna Haidar, Yasser Fadlallah, Hadi Sawaya, Abed Ellatif Samhat

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Joint optimization of transmission and edge offloading for energy-aware point cloud video streaming by LIU Wei, ZHU Yule, FU Chen, WANG Xi

“…A joint optimization model was established in this scheme to maximize the quality of user’s viewing experience and minimize the energy consumption of terminal device under the constraints of network resources, terminal and edge computing resources. …”
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Bipolar Morphological Neural Networks: Gate-Efficient Architecture for Computer Vision by Elena E. Limonova, Daniil M. Alfonso, Dmitry P. Nikolaev, Vladimir V. Arlazarov

“…Simultaneously, for different classes of computing architectures of the computer, the optimal neural network models will differ. …”
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