A Novel Multi-Task and Ensembled Optimized Parallel Convolutional Autoencoder and Transformer for Speech Emotion Recognition by Zahra Sharifzadeh Jafari, Sanaz Seyedin

Get full text

Optimizing anomaly detection models for edge IIoT with an enhanced firefly algorithm-based hyperparameter tuning strategy by Mohemmed Yousuf Rahamathulla, Mangayarkarasi Ramaiah

“…Security issues in the Industrial Internet of Things (IIoT) have grown more serious as industrial automation rises as these networks are especially prone to cyberattacks. By means of adaptive attack detection models, machine learning (ML) presents a potential solution. …”
Get full text

Optimized Blade Design of Counter-Rotating-Type Pump-Turbine Unit Operating in Pump and Turbine Modes by Jin-Woo Kim, Jun-Won Suh, Young-Seok Choi, Kyoung-Yong Lee, Toshiaki Kanemoto, Jin-Hyuk Kim

“…The hub and tip blade angles of the rear impeller (in the pump mode) were selected as the design variables by conducting a sensitivity test. An optimization process based on steady flow analysis was conducted using a radial basis neural network surrogate model with Latin hypercube sampling. …”
Get full text

A multi-objective aerodynamic performance optimization of a centrifugal vacuum pump and the flow physics analysis by Zhanyuan Gu, Jiangtao Zhang, Wei Zhang, Yikun Wei

“…The backpropagation neural network was employed as the surrogate model, and the multi-objective optimization was performed using the non-dominated sorting genetic algorithm. …”
Get full text

Improved Artificial Bee Colony Optimization Underwater Localization Algorithm by Logistic Chaos Mapping and Differential Evolution by Jiaxing CHEN, Yang LIU, Xiaoqian LIU, Zhihua LIU

“…Moreover, in terms of maximum and average error, the LDIABC algorithm exhibited a lower localization error than the other algorithms, indicating an effective optimization effect.Conclusions The LDIABC algorithm has proven effective in improving convergence speed and preventing the process from becoming trapped in local optima during iterations. …”
Get full text

Grape vine (Vitis vinifera) yield prediction using optimized weighted ensemble machine learning approach by Nobin Chandra Paul, Pratapsingh S. Khapte, Navyasree Ponnaganti, Sushil S. Changan, Sangram B. Chavan, K. Ravi Kumar, Dhananjay D. Nangare, K. Sammi Reddy

“…Additionally, three ensemble approaches-Simple Averaging, Weighted Averaging, and Ridge Regression-based ensemble models were implemented to improve prediction accuracy. …”
Get full text

Water desalination using waste heat recovery of thermal power plant in tropical climate; optimization by AI by Ehsanolah Assareh, Mohammad Firoozzadeh, Mohammad Zoghi, Ali Zare, Yasaman Ghazi, Ali Shahin-Banna

“…The optimization process is facilitated by artificial neural networks and genetic algorithms, utilizing EES and MATLAB software. …”
Get full text

Deep learning-based dual optimization framework for accurate thyroid disease diagnosis using CNN architectures by Zeeshan Ali Haider, Nasser A Alsadhan, Fida Muhammad Khan, Waleed Al-Azzawi, Inam Ullah Khan, Inam Ullah

“…Dual-OptNet shows the most accurate and generalizability results in classifying the thyroid disease with an average and best classification accuracy of 97% from a dual-step optimized using Adam and SGD. …”
Get full text

Hierarchically Federated Learning in Wireless Networks: D2D Consensus and Inter-Cell Aggregation by Jie Zhang, Li Chen, Yunfei Chen, Xiaohui Chen, Guo Wei

“…However, it is difficult to apply DFL to a multi-cell scenario due to inadequate model averaging and cross-cell device-to-device (D2D) communications. …”
Get full text

Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning by Qingli Liu, Yongjie Ma

“…Abstract In highly dynamic vehicular networking scenarios, when Vehicle-to-Infrastructure links and Vehicle-to-Vehicle links share spectrum resources, the traditional distributed resource allocation method lacks global optimization and fails to respond to environmental changes in a timely manner, which leads to low spectral efficiency of the system. …”
Get full text

Joint user association and power control scheme based on energy consumption and QoE in heterogeneous network by Shiyu JI, Liangrui TANG, Shuxian LI, Shimo DU

“…Based on multi-objective optimization,a joint user association and power control scheme was proposed in heterogeneous network environment,aiming to reduce the system energy consumption and improve user quality of experience.The scheme took the system energy consumption minimum and the average user quality of experience maximum as objective functions and translated the joint user association and power control to multi-objective problem.Then,the differential evolution optimization algorithm and TOPSIS algorithm was used to solve the multi-objective problem.Simulation results show that the scheme can efficiently reduce the system energy consumption and improve the user quality of experience.…”
Get full text

A new approach for diabetes risk detection using quadratic interpolation flower pollination neural network by Yulianto Triwahyuadi POLLY, Adriana FANGGIDAE, Juan Rizky Mannuel LEDOH, Clarissa Elfira AMOS PAH, Bertha S. DJAHI, Kisan Emiliano Rape TUPEN

“… This study aims to evaluate and compare five algorithms in diabetes detection, namely Flower Pollination Neural Network (FPNN), Particle Swarm Optimization Neural Network (PSONN), Bat Artificial Neural Network (BANN), Stochastic Gradient Descent (SGD), and Quadratic Interpolation Flower Pollination Neural Network (QIFPNN). …”
Get full text

AI-Driven Aerial Relay Placement and Power Allocation for Enhanced Secrecy in Untrusted UAV-Enabled Networks by Lefteris Tsipi, Emmanouel T. Michailidis, Michail Karavolos, Demosthenes Vouyioukas, Athanasios G. Kanatas

“…Conventional optimization methods often fail to effectively capture the intricate, dynamic nature of such networks, thereby limiting their ability to ensure adaptive secrecy optimization. …”
Get full text

User-Centric Federated Learning: Trading off Wireless Resources for Personalization by Mohamad Mestoukirdi, Matteo Zecchin, David Gesbert, Qianrui Li

Get full text

Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution. by Qi Jin

“…On this basis, considering the data transmission in the core network in the power IoT, a multi-path low-latency routing optimization transmission model based on software-defined network task allocation is designed by combining the software-defined network controller and task allocation concept. …”
Get full text

Improving IoRT Networks: Cross-Tier Resource Allocation for Multi-Antenna UAV Relays in SAGIN by Zahra Khodadadi, Foroogh S. Tabataba, Mohammad Sadegh Fazel, Mehdi Naderi Soorki, Halim Yanikomeroglu

“…In response to reducing power consumption while reducing equipment and maintaining high data rate requirements in Space-Air-Ground Integrated Networks (SAGIN) as part of the Internet of Remote Things (IoRT) networks, this paper proposes a system model and optimization scheme. …”
Get full text

Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network by Feng-Ping An

“…Therefore, this paper starts from the perspective of network optimization and improves the nonlinear modeling ability of the network through optimization methods. …”
Get full text

Physarum-inspired multi-parameter adaptive routing protocol for coal mine hybrid wireless mesh networks by Guangzhi Han, Haifeng Jiang, Liansheng Lu, Shanshan Ma, Shuo Xiao

“…In this article, we use Physarum-inspired autonomic optimization model to design a Physarum-inspired multi-parameter adaptive routing protocol to improve the service quality of coal mine hybrid wireless mesh networks. …”
Get full text

A Fairness Relation Based on the Asymmetric Choquet Integral and Its Application in Network Resource Allocation Problems by Aoi Honda, Mario Köppen

“…The recent problem of network resource allocation is studied where pairs of users could be in a favourable situation, given that the allocation scheme is refined by some add-on technology. …”
Get full text

A Multiobjective Evolutionary Algorithm for Energy-Efficient Cooperative Spectrum Sensing in Cognitive Radio Sensor Network by Weirong Liu, Gaorong Qin, Shuo Li, Jian He, Xiaoyong Zhang

“…The main objective of the proposed algorithm is to minimize the network energy consumption subjected to constraints on the detection performance by optimally deriving the censoring and sleeping probabilities. …”
Get full text