Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers by Anupam Yadav, Rifat Hussain, Madhu Shukla, Jayaprakash B, Rishiv Kalia, S. Prince Mary, Chou-Yi Hsu, Manoj Kumar Mishra, Kashif Saleem, Mohammed El-Meligy

“…Meta-heuristic algorithms offer an alternative to traditional gradient-based optimizers for improving DNNs performance. …”
Get full text

Passivity-Based Control for Rocket Launcher Position Servo System Based on ADRC Optimized by IPSO-BP Algorithm by Rong-lin Wang, Bao-chun Lu, Yuan-long Hou, Qiang Gao

“…Furthermore, to improve the learning capability, the improved PSO algorithm is adopted to optimize the learning rates of the back propagation neural networks. …”
Get full text

Optimizing SVC placement for enhanced voltage stability using a novel index and hybrid ABC-PSO algorithm by Hafizur Rahman, Roman Mia, Mustafizur Rahman, Md. Faiyaj Ahmed Limon, Md. Shahid Iqbal, Md. Fahad Jubayer, Md. Rabiul Karim, Md. Janibul Alam Soeb

“…The ABC-PSO hybrid algorithm converges very quickly to optimal solutions in 10 to 40 iterations and outperforms five state-of-the-art optimizers with a 100 % success rate for the IEEE 14-bus system and a mean computation time of 0.041 s per iteration. …”
Get full text

ClipQ: Clipping Optimization for the Post-Training Quantization of Convolutional Neural Network by Yiming Chen, Hui Zhang, Chen Zhang, Yi Liu

“…In response to the issue that post-training quantization leads to performance degradation in mobile deployment, as well as the problem that the balanced consideration of quantization deviation by Clipping optimization techniques limits the improvement of quantization accuracy, this article proposes a novel clipping optimization method named ClipQ, which pays different attention to the parameters, aiming to preferentially reduce the quantization deviation of important parameters. …”
Get full text

Optimal Design Method of a Hybrid CSP-PV Plant Based on Genetic Algorithm Considering the Operation Strategy by Rongrong Zhai, Ying Chen, Hongtao Liu, Hao Wu, Yongping Yang

“…In this paper, the operation strategy of the CSP-PV system is proposed for parabolic trough CSP system and PV system which are now commercially operated. Genetic algorithm is used to optimize the design of the system and calculate PV-installed capacity, battery capacity, and storage capacity of CSP system, making the system to achieve the lowest cost of electricity generation. …”
Get full text

GAGAN: Enhancing Image Generation Through Hybrid Optimization of Genetic Algorithms and Deep Convolutional Generative Adversarial Networks by Despoina Konstantopoulou, Paraskevi Zacharia, Michail Papoutsidakis, Helen C. Leligou, Charalampos Patrikakis

“…In this paper, we propose a novel hybrid optimization method that integrates Genetic Algorithms (GAs) to improve the training process of Deep Convolutional GANs (DCGANs). …”
Get full text

Quad Rapidly-Exploring Random Tree Star Algorithm With Improved Potential Force for Unmanned Aerial Vehicle Path Planning by Peng Bian, Jiaming Fan, Yang Liu, Xia Chen, Yu Wang

“…Rapidly-exploring random tree star (RRT*) has attracted intensive attention in track planning due to its asymptotic optimal properties. However, the RRT* algorithm plans costly trajectory paths. …”
Get full text

Revalorization of Vinasse as a Farmland Improver Through Multi-Objective Genetic Algorithms: A Circular Economy Approach by Aarón Montiel-Rosales, Nayeli Montalvo-Romero, Gregorio Fernández-Lambert, Horacio Bautista-Santos, Yair Romero-Romero, Juan Manuel Carrión-Delgado

“…This study showed that vinasse improved soil fertility, quality, and health, with an optimal ratio of mixture formed by 40% vinasse and 60% irrigation water. …”
Get full text

Optimal Lower Step Height of Tunnel Excavation Designs by Using the Non-Dominated Sorting Genetic Algorithm-II by Shaoqing Niu, Jinwen Wu, Jinchang Zhao, Junjie Pei

Get full text

Cloud-based optimized deep learning framework for automated glaucoma detection using stationary wavelet transform and improved grey-wolf-optimization with ELM approach by Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, Anuradha S. Kanade, Mohammad Shameem, Harendra S. Jangwan, P.M. Ashok Kumar, Abu Taha Zamani

“…Finally, an improved gray wolf optimization algorithm integrated with an extreme learning machine (IMGWO-ELM) classifies the images as either healthy or glaucomatous. …”
Get full text

Resource scheduling algorithm of satellite communication system for future multi-beam dense networking by Yuanzhi HE, Cong PENG, Jihong YU, Yun LIU

“…The resource scheduling problem of satellite communication systems under the condition of high-dynamic and resource limitation was studied.A resource scheduling model for satellite communication systems was established based on time window, energy consumption, number of channels, user priority and task suddenness.Considering the disadvantages of slow initial search speed and weak local search ability, the improved ant colony algorithm based on construction of initial solution set and extra pheromone deposition was proposed to solve the resource scheduling problem.The optimization characteristics of the number of completed tasks, priority and scheduling completion time were simulated and analyzed.The results show that the algorithm has a fast convergence rate.Compared with the same type optimization algorithm, the algorithm has high scheduling efficiency, therefore, it is suitable for scheduling satellite communication system resources for multi-beam dense networking in the future.…”
Get full text

Enhanced Underwater Image Restoration and Clarity Optimization Using Advanced Digital Image Processing Techniques by Gopirajan Punniyakotti Varadharajan, Pradeep T., Charan R.

Get full text

Joint energy efficiency and spectral efficiency optimization algorithm for UDN under the restriction of interference threshold and backhaul capacity by Xuanli WU, Xu CHEN

“…Aiming at the scenarios which consider the constraint of backhaul capacity restriction and interference threshold in ultra-dense networks (UDN),an integer linear programming (ILP) and Lagrangian dual decomposition (LDD) based joint optimization algorithm of energy efficiency and spectrum efficiency was proposed.In the proposed algorithms,the user association problem with the constraint of limited backhaul capacity was modelled as an ILP problem and then finished the connection between the user and the base station of microcell by solving this problem with dynamic programming method.Therefor,Lagrangian dual decomposition (LDD) was applied in an iteration algorithm for spectrum resource allocation and power allocation.The simulation results show that compared with traditional schemes,the proposed algorithm can significantly improve the energy efficiency and spectrum efficiency of system and use the microcell’s load capacity more efficiently.…”
Get full text

Joint energy efficiency and spectral efficiency optimization algorithm for UDN under the restriction of interference threshold and backhaul capacity by Xuanli WU, Xu CHEN

“…Aiming at the scenarios which consider the constraint of backhaul capacity restriction and interference threshold in ultra-dense networks (UDN),an integer linear programming (ILP) and Lagrangian dual decomposition (LDD) based joint optimization algorithm of energy efficiency and spectrum efficiency was proposed.In the proposed algorithms,the user association problem with the constraint of limited backhaul capacity was modelled as an ILP problem and then finished the connection between the user and the base station of microcell by solving this problem with dynamic programming method.Therefor,Lagrangian dual decomposition (LDD) was applied in an iteration algorithm for spectrum resource allocation and power allocation.The simulation results show that compared with traditional schemes,the proposed algorithm can significantly improve the energy efficiency and spectrum efficiency of system and use the microcell’s load capacity more efficiently.…”
Get full text

Optimizing the neural network and iterated function system parameters for fractal approximation using a modified evolutionary algorithm by Sana Abdulla, K. Mahipal Reddy

“…In this study, we propose an evolutionary optimization strategy to enhance the accuracy and adaptability of RFC splines by optimizing their scaling factor and shape parameters using our novel Fractal Differential Evolution (FDE) algorithm. …”
Get full text

Research on the Optimization of the PID Control Method for an EOD Robotic Manipulator Using the PSO Algorithm for BP Neural Networks by Yunkang Zhou, Xiaohui He, Faming Shao, Xiangpo Zhang

“…This study proposes a PID control strategy optimized by the particle swarm optimization (PSO) algorithm for a backpropagation (BP) neural network and simulates the system’s step response for analysis. …”
Get full text

Automatic detection and prediction of COVID-19 in cough audio signals using coronavirus herd immunity optimizer algorithm by G. Ayappan, S. Anila

Get full text

Multi-Population Optimization Framework Based on Plant Evolutionary Strategy and Its Application to Engineering Design Problems by Hongwei Cheng, Jun Li, Xiaoming Zhang, Tingjuan Li, Panpan Zhang

“…It outperforms other state-of-the-art optimization algorithms, demonstrating significant improvements in global optimization, solution accuracy, and convergence speed. …”
Get full text

An integrated stacked convolutional neural network and the levy flight-based grasshopper optimization algorithm for predicting heart disease by Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Majad Mansoor, Filippo Sanfilippo

“…This study proposes a novel hybrid model integrating a Stacked Convolutional Neural Network (SCNN) with the Levy Flight-based Grasshopper Optimization Algorithm (LFGOA) to address this challenge. …”
Get full text

Incorporating echo state network and sand cat swarm optimization algorithm based on quantum for named entity recognition by Fang Huang, Baocheng Wang, Jafar Safarzadeh

“…The main contribution of this study is the combination of QSCSO with ESN, which improves the model’s capacity to comprehend long-term dependencies and effectively optimize hyperparameters. …”
Get full text