Machine Learning Optimization Techniques: A Survey, Classification, Challenges, and Future Research Issues

Archives of Computational Methods in Engineering, Год журнала: 2024, Номер unknown

Опубликована: Март 29, 2024

Язык: Английский

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Research on Image Recognition and Classification Algorithms in Cloud Computing Environment Based on Deep Neural Networks

IEEE Access, Год журнала: 2025, Номер 13, С. 19728 - 19754

Опубликована: Янв. 1, 2025

Язык: Английский

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Techniques employed in distributed cognitive radio networks: a survey on routing intelligence

Multimedia Tools and Applications, Год журнала: 2024, Номер unknown

Опубликована: Апрель 10, 2024

Язык: Английский

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Denoising and segmentation in medical image analysis: A comprehensive review on machine learning and deep learning approaches

Multimedia Tools and Applications, Год журнала: 2024, Номер unknown

Опубликована: Май 17, 2024

Язык: Английский

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Large Language Models Meet Next-Generation Networking Technologies: A Review

Future Internet, Год журнала: 2024, Номер 16(10), С. 365 - 365

Опубликована: Окт. 7, 2024

The evolution of network technologies has significantly transformed global communication, information sharing, and connectivity. Traditional networks, relying on static configurations manual interventions, face substantial challenges such as complex management, inefficiency, susceptibility to human error. rise artificial intelligence (AI) begun address these issues by automating tasks like configuration, traffic optimization, security enhancements. Despite their potential, integrating AI models in engineering encounters practical obstacles including configurations, heterogeneous infrastructure, unstructured data, dynamic environments. Generative AI, particularly large language (LLMs), represents a promising advancement with capabilities extending natural processing translation, summarization, sentiment analysis. This paper aims provide comprehensive review exploring the transformative role LLMs modern engineering. In particular, it addresses gaps existing literature focusing LLM applications design planning, implementation, analytics, management. It also discusses current research efforts, challenges, future opportunities, aiming guide for networking professionals researchers. main goal is facilitate adoption networking, promoting more efficient, resilient, intelligent systems.

Язык: Английский

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Blockchain 6G-Based Wireless Network Security Management with Optimization Using Machine Learning Techniques

Sensors, Год журнала: 2024, Номер 24(18), С. 6143 - 6143

Опубликована: Сен. 23, 2024

6G mobile network technology will set new standards to meet performance goals that are too ambitious for 5G networks satisfy. The limitations of have been apparent with the deployment more and networks, which certainly encourages investigation as answer future. This research includes fundamental privacy security issues related technology. Keeping an eye on real-time systems requires secure wireless sensor (WSNs). Denial service (DoS) attacks mark a significant vulnerability WSNs face, they can compromise system whole. proposes novel method in blockchain 6G-based management optimization using machine learning model. In this research, deployed is carried out user datagram transport protocol reinforcement projection regression. Then, completed artificial democratic cuckoo glowworm remora optimization. simulation results based various parameters regarding throughput, energy efficiency, packet delivery ratio, end–end delay, accuracy. order minimise traffic, it also offers capacity determine optimal node path selection data transmission. proposed technique obtained 97% 95% 96% accuracy, 50% 94% ratio.

Язык: Английский

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Analysis of Mutual Inductance Characteristics of Rectangular Coils Based on Double-Sided Electromagnetic Shielding Technology and Study of the Effects of Positional Misalignment

Electronics, Год журнала: 2025, Номер 14(1), С. 200 - 200

Опубликована: Янв. 5, 2025

In wireless power transfer systems, the relative positional misalignment between transmitting and receiving coils significantly impacts system’s mutual inductance characteristics, thereby constraining output stability transmission efficiency optimization potential. Hence, accurate formulas for calculating are crucial optimizing coil structures achieving stability. This study focuses on characteristics of rectangular under conditions in a dual-sided electromagnetic shielding environment. Initially, research deduces incident magnetic flux density induced by current through dual Fourier transform vector potential method. Subsequently, Maxwell’s equations boundary employed to analytically examine eddy currents within layer, allowing calculation reflected density. Based these analyses, derives formula using A prototype was built experimental verification. The experiment results show that maximum error measured calculated result is less than 3.8%, which verifies feasibility accuracy proposed Simulations empirical validation demonstrate superior practicality formula. not only offers an innovative technological pathway enhancing systems but also provides solid theoretical foundation guiding framework design optimization.

Язык: Английский

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RL-EAR: reinforcement learning-based energy-aware routing for software-defined wireless sensor network

The Journal of Supercomputing, Год журнала: 2025, Номер 81(3)

Опубликована: Фев. 12, 2025

Язык: Английский

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Optimized Transformer- Basde Security for Vehicular Network Communication Against Denial- of - Service Attack

Salud Ciencia y Tecnología - Serie de Conferencias, Год журнала: 2025, Номер 4, С. 1424 - 1424

Опубликована: Янв. 21, 2025

Objective: A Vehicular Ad-Hoc Network (VANET) is one of the crucial elements an Intelligent Transport System (ITS) and plays a significant role in security communication. VANETs are susceptible to Denial Service (DoS) attacks, which inherent threat performance such networks, requiring more sophisticated detection countermeasures. Methods: In response this problem, Spatial Hyena Security Transformer Model (SHSTM) introduced improve use Ad-hoc communication against DoS attacks. The network nodes set up enable Vehicle-to-Vehicle (V2V) communication; SHSTM constantly detects each node detect filter out attack targets. model includes effective Cluster Head (CH) selection approach based on traffic patterns enhance security.Results: Comparative measurements conducted positions before after attacks show enhanced overall terms Packet Delivery Ratio (PDR), Throughput (NT), Energy Consumption (EC), End-to-End Delay (EED), Attack Detection (ADR). attains NT 3.91 Mbps, minimal EC 1.02 mJ, highest PDR 99.04%, EED 0.0206 seconds, higher ADR 98%. Conclusions: design proposed proved improvement performance, outperforms existing state-of-the-art technique. Hence, it considered potential solution address VANET.

Язык: Английский

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New Frontiers in Machine Learning Optimization

Advances in computational intelligence and robotics book series, Год журнала: 2025, Номер unknown, С. 427 - 454

Опубликована: Янв. 10, 2025

Machine learning (ML) optimization techniques serve as essential for training models to achieve high performance in a diverse areas. This chapter offers thorough summary of machine techniques. analysis the development over time. A number common constraints are also discussed. Developing model that works effectively and provides accurate predictions certain set instances is main objective ML. We require ML accomplish that. The practice modifying hyper parameters with an technique minimize cost function called optimization. Because indicates difference between actual value estimated parameter predicted by model, it crucial reduce it. will provide general explanation workings drawbacks strategies. Numerous advancements have been put forth this chapter.

Язык: Английский

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