Deep Learning for Telecom Self-Optimized Networks: Benefits and Implications by Farah Alhaqui, Iyad Lahsen-Cherif, Mariam Elkhechafi, Ahmed Elkhadimi

“…These high-precision forecasts significantly improved network awareness, enabling the deployment of energy optimization strategies that reduced energy consumption across 1,100 base stations by an average of 11% per station.…”
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Cooperative and Adaptive Load-Aware Handover Optimization in Heterogeneous Networks by Kihoon Kim, Eunsok Lee, Chanbin Bae, Heewon Kim, Sangheon Pack

“…The simulation results confirm that the proposed scheme mitigates connectivity degradation while effectively reducing the average MBS load by 19.6% and decreasing the number of handovers, ping-pong handovers, and radio link failures throughout the network by 25.0%, 41.9%, and 38.2%, respectively.…”
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Optimization of machine learning methods for de-anonymization in social networks by Nurzhigit Smailov, Fatima Uralova, Rashida Kadyrova, Raiymbek Magazov, Akezhan Sabibolda

“…In experiments conducted on real and synthetic data, the optimized models consistently outperform baseline methods on average. …”
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Application of Optimized Convolution Neural Network Model in Mural Segmentation by Zhiqiang Chen, Leelavathi Rajamanickam, Xiaodong Tian, Jianfang Cao

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Optimizing Wireless Sensor Network longevity with hierarchical chain-based routing and vertical network partitioning techniques by V. Rama Krishna, Vuppala Sukanya, Mohd Abdul Hameed

“…The suggested method has the potential to enhance the average network longevity substantially when compared to existing routing techniques. …”
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Enhancing network Quality of Experience based on Artificial Neural Networks by Ali Mohammed, Rana Ghani

“…The proposed solution optimizes performance across various types of network traffic, enabling efficient handling of voice, video, and other data packets. …”
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Optimization Strategies for Urban Waterlogging Warning in Complex Environments: Based on Particle Swarm Optimization and Deep Neural Networks by Xiande Hu, Fenfei Gu

“…To better address these issues, this article combines particle swarm optimization (PSO) and deep neural networks (DNN) to explore the construction of early warning models in depth. …”
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Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

“…The inherent characteristics of unbalanced three-phase distribution networks can have negative technical and financial effects. …”
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Optimizing Handover Parameters by Q-Learning for Heterogeneous Radio-Optical Networks by Sihua Shao, Guanxiong Liu, Abdallah Khreishah, Moussa Ayyash, Hany Elgala, Thomas D. C. Little, Michael Rahaim

“…Case studies are performed to validate the considerable gain in terms of average throughput by optimizing <inline-formula><tex-math notation="LaTeX">$TTT$</tex-math></inline-formula>s. …”
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Coverage optimization algorithm based on VF-CS in mobile sensor network by Guanghui LI, Shihong HU

“…A random placement of large-scale sensor network in the outdoor environment often causes low coverage.An area coverage optimization algorithm of mobile sensor network (MSN) based on virtual force perturbation and Cuckoo search (VF-CS) was proposed.Firstly,the virtual force of the sensor nodes within the Thiessen polygon was analyzed based on the partitioning of Voronoi diagram of the monitoring area.Secondly,the force of polygon vertices and neighbor nodes was taken as the perturbation factor for updating the node’s location of the Cuckoo search (CS).Finally,the VF-CS guided the node to move so as to achieve the optimal coverage.The simulation results demonstrate that the proposed algorithm has higher coverage and shorter average moving distance of nodes than the Voronoi diagram based algorithms in literatures.…”
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Routing optimization method based on GPCR for vehicular Ad Hoc network by Zhiru GU, Min LI, Yonghong LONG, Xiaohua SHU, Qing RONG

“…To improve the performance in sparse networks,local optimum,and routing loop in the greedy perimeter coordinator routing (GPCR) protocol,the weighted-GPCR (W-GPCR) protocol was proposed.The relationship between vehicle node routing and other parameters such as the Euclidean distance between node pairs,moving direction and density was profoundly analyzed,the composite parameter weighted model was established and the calculation method was designed for the existing routing problems,the weighted parameter ratio was selected adaptively in different scenarios,so as to obtain the optimal next-hop relay node.In order to verify the performance of the W-GPCR method,the proposed method was compared with the existing methods such as the traditional geographic perimeter stateless routing (GPSR) protocol,GPCR and so on,and the results show that the proposed method is superior to the package delivery ratio,end-to-end delay,and average hop count.…”
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An Optimized Data Obtaining Strategy for Large-Scale Sensor Monitoring Networks by Yan Wang, Junlu Wang, Fengtong Wang, Ling Wang, Wei Wei

“…The OFS optimization strategy can prolong network lifetime, reduce the transmission bandwidth resources, and reduce average energy consumption of the cluster head and network energy consumption.…”
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The Improved Antlion Optimizer and Artificial Neural Network for Chinese Influenza Prediction by Hongping Hu, Yangyang Li, Yanping Bai, Juping Zhang, Maoxing Liu

“…The experimental results show that the proposed IALO outperforms SCA, PSO, MFO, MVO, and ALO according to the average values and the convergence speeds. And the proposed IALO is tested to optimize the parameters of BP neural network for predicting the Chinese influenza and the predicted model is built, written as IALO-BPNN, which is against the models: BPNN, SCA-BPNN, PSO-BPNN, MFO-BPNN, MVO-BPNN, and ALO-BPNN. …”
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Coverage Capacity Optimization for Mobile Sensor Networks Based on Evolutionary Games by Jianhua Liu, Guangxue Yue, Shigen Shen, Huiliang Shang, Hongjie Li

“…The optimal and distributed provisioning of high coverage capacity in mobile sensor networks is known as a fundamental but hard problem. …”
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Explainable Model of Fusion Network With Enhanced Optimization Approach for Tuberculosis Diagnosis by C. R. Dhivyaa, K. Nithya, C. Sathiya Kumar, R. Sudhakar

“…These subsets are correlated by ensemble model, and the optimal features from EAMSO are input into an Artificial Neural Network for classification. …”
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An Overview of Performance Analysis and Optimization in Coexisting Satellites and Future Terrestrial Networks by Sirine Ben Ati, Hayssam Dahrouj, Mohamed-Slim Alouini

“…To this end, this manuscript surveys the advances in optimization and performance analysis methods in coexisting satellites networks and future wireless systems. …”
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Optimizing urban transportation network reliability by analyzing road traffic accidents by Isaac Pemberthy, Eduard Gañan-Cardenas

“…This study addresses these challenges by integrating statistical analysis and optimization modeling to enhance the reliability of urban transportation networks through targeted interventions. …”
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Creating Balance on Bandwidth Consumption using Network Coding in Wireless Sensor Networks by Ehsan Kharati

“…The results show that the proposed model and algorithm, due to informed routing and NC, can improve the parameters of the average required time to find the route optimal, the total amount of virtual flow in networkâs edges, the average latency end-to-end of the network, the consumed bandwidth, the average lifetime of the network and the consumed energy, or not very weak compared to other models. …”
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Coordinated Jamming and Poisoning Attack Detection and Mitigation in Wireless Federated Learning Networks by Sofia Barkatsa, Maria Diamanti, Panagiotis Charatsaris, Stefanos Voikos, Eirini Eleni Tsiropoulou, Symeon Papavassiliou

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Optimal energy efficiency routing strategy based on community in mobile social network by Ying PENG, Nao WANG, Gao-cai WANG

“…An optimal energy efficiency routing strategy based on community was proposed,which minimized the network energy consumption under the given delay constraint.Firstly the expected energy consumption and delay of message delivery in the connected network were obtained through Markov chain.Then the comprehensive cost function for delivering message from source node to destination node was designed,which was combined with energy consumption and delay.Thus,the optimization function to comprehensive cost of relay node delivering message was obtained,and further the reward function of relay node was gotten.Finally the optimal expected reward of optimal relay node was achieved using the optimal stopping theory,so as to realize the optimal energy efficiency routing strategy.In simulations,the average energy consumption,the average delay and the average delivery ratio of routing optimization strategy were compared with those of other routing strategies in related literatures.The results show that the strategy proposed has smaller average energy consumption,shorter average delay and higher average delivery ratio,gaining better energy consumption optimization effect.…”
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