Portable sinks assume a vital part in information assortment within wireless sensor networks (WSNs), offering dynamic and flexible solutions to address the limitations of static sink-based architectures. Unlike their ...
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This study investigates using machine learning (ML), the Internet of Things (IoT), and cloud computing to predict cardiovascular diseases. Integrating these advanced technologies in healthcare enables the collection, ...
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The following paper proposes the SISRR framework for knowledge centric, semantically inclined, framework for software requirement recommendations. This framework is intelligent driven by integrating semantically incli...
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In the engineering, Procurement, and Construction (EPC) sector, accurate cost estimations during the tendering phase are crucial for maintaining competitiveness, especially with constrained project schedules and risin...
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Secure UPI specializes in developing an advanced fraud detection gadget the usage of the effective XGBoost device getting to know set of rules to create an advanced fraud identity device. XGBoost is a properly-proper ...
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Cybersecurity has always been the focus of Internet *** LDoS attack is an intelligent type of DoS attack,which reduces the quality of network service by periodically sending high-speed but short-pulse attack *** of it...
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Cybersecurity has always been the focus of Internet *** LDoS attack is an intelligent type of DoS attack,which reduces the quality of network service by periodically sending high-speed but short-pulse attack *** of its concealment and low average rate,the traditional DoS attack detection methods are challenging to be *** existing LDoS attack detection methods generally have the problems of high FPR and FNR.A cloud model-based LDoS attack detection method is proposed,and a classifier based on SVM is used to train and classify the feature *** detection method is verified and tested in the NS2 simulation platform and Test-bed network *** with the existing research results,the proposed method requires fewer samples,and it has lower FPR and FNR.
As global energy demands escalate, effective management of electrical grids and reducing carbon emissions have become critical objectives. This paper proposes a novel system which employs Explainable Artificial Intell...
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Medical image segmentation plays an important role in computer-aid diagnosis. In the past years, convolutional neural networks, especially the UNet-based architectures with symmetric U-shape encoder-decoder structure ...
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Twitter and other social media platforms have evolved into crucial sources of information and communication for billions of people across the world. The massive amount of data collected on these platforms enables insi...
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The flow shop scheduling problem is important for the manufacturing *** flow shop scheduling can bring great benefits to the ***,there are few types of research on Distributed Hybrid Flow Shop Problems(DHFSP)by learni...
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The flow shop scheduling problem is important for the manufacturing *** flow shop scheduling can bring great benefits to the ***,there are few types of research on Distributed Hybrid Flow Shop Problems(DHFSP)by learning assisted *** work addresses a DHFSP with minimizing the maximum completion time(Makespan).First,a mathematical model is developed for the concerned ***,four Q-learning-assisted meta-heuristics,e.g.,genetic algorithm(GA),artificial bee colony algorithm(ABC),particle swarm optimization(PSO),and differential evolution(DE),are *** to the nature of DHFSP,six local search operations are designed for finding high-quality solutions in local *** of randomselection,Q-learning assists meta-heuristics in choosing the appropriate local search operations during ***,based on 60 cases,comprehensive numerical experiments are conducted to assess the effectiveness of the proposed *** experimental results and discussions prove that using Q-learning to select appropriate local search operations is more effective than the random *** verify the competitiveness of the Q-learning assistedmeta-heuristics,they are compared with the improved iterated greedy algorithm(IIG),which is also for solving *** Friedman test is executed on the results by five *** is concluded that the performance of four Q-learning-assisted meta-heuristics are better than IIG,and the Q-learning-assisted PSO shows the best competitiveness.
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