Achieving Faster and Smarter Chest X-Ray Classification With Optimized CNNs by Hassen Louati, Ali Louati, Khalid Mansour, Elham Kariri

“…Finally, model compression through filter pruning, driven by evolutionary algorithms, trims redundant parameters to improve computational efficiency while preserving model accuracy. …”
Get full text

Quantum Adiabatic Optimization with Rydberg Arrays: Localization Phenomena and Encoding Strategies by Lisa Bombieri, Zhongda Zeng, Roberto Tricarico, Rui Lin, Simone Notarnicola, Madelyn Cain, Mikhail D. Lukin, Hannes Pichler

“…On the QuEra Aquila neutral atom machine, we observe such localization and its effect on the success probability of finding the correct solution to the encoded optimization problem. Finally, we propose quantum-aware modifications of the encoding scheme that avoid this quantum bottleneck and lead to an exponential improvement in the adiabatic performance. …”
Get full text

Three-Dimensional Drone Cell Placement: Drone Placement for Optimal Coverage by Aniket Basu, Hooman Oroojeni, Georgios Samakovitis, Mohammad Majid Al-Rifaie

“…Algorithmic diversity has been explored, leading to several modifications and improvements in the implemented models. …”
Get full text

Enhanced Harmony Search Algorithm for Maximum Power Point Tracking Under Partial Shading in PV Systems by Geon Hee Lee, Zong Woo Geem, Jehyuk Won

“…The results show that the proposed algorithm outperforms conventional HS and particle swarm optimization algorithms in terms of the number of iterations and convergence time, while maintaining a similar level of accuracy.…”
Get full text

Smart energy management for revenue optimization and grid independence in an Indian RDS by T. Yuvaraj, M. Thirumalai, M. Dharmalingam, Sudhakar Babu Thanikanti, Sanjeevikumar Padmanaban

“…The framework employs the hunter-prey optimization algorithm (HPOA) to enhance appliance scheduling, renewable energy integration (PV, WT, EV, BESS), and dynamic tariff management while addressing uncertainties in electric vehicle (EV) usage and renewable distributed generation (RDG) output. …”
Get full text

Dynamic Collaborative Optimization Method for Real-Time Multi-Object Tracking by Ziqi Li, Dongyao Jia, Zihao He, Nengkai Wu

“…Experiments conducted on multiple public datasets, including MOT17, MOT20, and VisDrone-MOT, demonstrate that this method remarkably improves tracking accuracy while maintaining real-time performance. …”
Get full text

The optimization path of agricultural industry structure and intelligent transformation by deep learning by Xingchen Pan, Jinyu Chen

“…Subsequently, a hybrid optimization method is designed, combining the Genetic Algorithms with particle swarm optimization to improve the model’s global search capability and local convergence speed. …”
Get full text

Connectivity-Enhanced 3D Deployment Algorithm for Multiple UAVs in Space–Air–Ground Integrated Network by Shaoxiong Guo, Li Zhou, Shijie Liang, Kuo Cao, Zhiqun Song

“…Finally, a height optimization algorithm is proposed to adjust the height of each UAV, completing the 3D deployment of multiple UAVs. …”
Get full text

Ant Colony Optimization Using Common Social Information and Self-Memory by Yoshiki Tamura, Tomoko Sakiyama, Ikuo Arizono

“…In this paper, to solve this problem, we introduce the ant system using individual memories (ASIM) aiming to improve the ability to solve TSP while maintaining the diversity of the behavior of each ant. …”
Get full text

COD Optimization Prediction Model Based on CAWOA-ELM in Water Ecological Environment by Lili Jiang, Liu Yang, Yang Huang, Yi Wu, Huixian Li, XiYan Shen, Meng Bi, Lin Hong, Yiting Yang, Zuping Ding, Wenjie Chen

“…In order to detect high error rate and poor convergence of the water ecological chemical oxygen demand (COD) prediction model, combining the limit learning machine (ELM) model and whale optimization algorithm, CAWOA is improved by the sin chaos search strategy, while the ELM optimizes the parameters of the algorithm to improve convergence speed, thus improving the generalization performance of the ELM. …”
Get full text

Efficient and Composable Masked AES S-Box Designs Using Optimized Inverters by Vedad Hadžic, Roderick Bloem

“…The masking of the AES S-Box is well studied, and most implementations use Canright’s F28 inverter design that decomposes operations in a larger field into a combination of multiplications, additions and inversions in a smaller field. While remarkable, Canright’s inverter design has a sub-optimal multiplicative depth, and can thus not take full advantage of recent developments in low-latency composable masking schemes. …”
Get full text

Selective opposition based constrained barnacle mating optimization: Theory and applications by Marzia Ahmed, Mohd Herwan Sulaiman, Md. Maruf Hassan, Md. Atikur Rahaman, Masuk Abdullah

“…We will later integrate opposition-based learning (OBL) with constrained BMO (C-BMO) to improve its exploratory behavior while retaining a quick convergence rate. …”
Get full text

Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

Get full text

Numerical modeling and neural network optimization for advanced solar panel efficiency by Udit Mamodiya, Indra Kishor, Mohammed Amin Almaiah, Monia Hamdi, Rami Shehab, Tayseer Alkhdour

“…Conventionally, such optimization techniques—MPPT (Maximum Power Point Tracking) along with heuristic algorithms—suffer significantly from slow adaptability and track sub optimality under dynamic environments. …”
Get full text

An Effective QoS-Aware Hybrid Optimization Approach for Workflow Scheduling in Cloud Computing by Min Cui, Yipeng Wang

“…Furthermore, an improved Whale Optimization Algorithm (WOA) based on Lévy flight is proposed. …”
Get full text

Optimized Ensemble Methods for Classifying Imbalanced Water Quality Index Data by Zaharaddeen Karami Lawal, Ali Aldrees, Hayati Yassin, Salisu Dan'azumi, Sujay Raghavendra Naganna, Sani I. Abba, Saad Sh. Sammen

“…In all experiments, XGBoost performed best individually, while SVM was worst. The ensemble models outperformed individuals, with the GridSearchCV ensemble achieving 97.3% accuracy, an improvement exceeding the existing literature’s models by 2.3%. …”
Get full text

AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

“…Moreover, the transition from a rule-based maintenance prediction system to a machine learning approach improved efficiency and accuracy. As a result of this transition, individual customer service visit rates increased by 30%, while corporate customer visits rose by 37%. …”
Get full text

Hyperspectral Estimation of Chlorophyll Content in Ginseng Fruit Leaves Based on Wavelet Transform and VCPA-GA Algorithm by Guo Jinfeng, Zhang Zhicong, Umut Hasan, Zhou Zhongye, Xu Wenyu, Yusup Ahmat

“…This is because the wavelet transform process has some errors that increase with the number of decomposition layers. (2) The VCPA-GA hybrid variable selection algorithm merges the strengths of the VCPA and GA, addressing the tendency of the VCPA to select fewer variables and overcoming GA's limitations in handling many variables which can lead to overfitting, providing a theoretical basis for estimating ginseng fruit LCC using hyperspectral remote sensing. (3) Among the four machine-learning models, predictions from to 1-2 and 6-7 layers were generally lower than those of the 0 layer, while predictions from the 3–5 layers are higher, showing an overall trend of initial increase followed by a decrease as the number of wavelet decomposition layers increased. (4) Ginseng fruit leaf hyperspectral data processed by the DWT-VCPA-GA algorithm with a 4-layer DWT spectrum yielded the best predictive performance in the BP-AdaBoost regression model, with R2=0.919, mean absolute percentage error = 2.090%, and relative percentage difference = 3.900. (5) After optimizing the BPNN regression model with various algorithms, only some optimized models improved their predictive performance and accuracy to a certain extent, making the choice of the right optimization algorithm crucial for model improvement.…”
Get full text

An efficient algorithm for pedestrian fall detection in various image degradation scenarios based on YOLOv8n by Jianhui Xun, Xuefeng Wang, Xiufang Wang, Xiaoliang Fan, Peishuai Yang, Zhifei Zhang

“…Additionally, the Cross Stage Partial Bottleneck with 2 Convolution Block (C2f) was optimized to reduce computational load and parameter count without compromising performance, while the Inner Extended Intersection over Union (Inner-EIoU) loss function was employed to improve bounding box regression accuracy and speed. …”
Get full text

Reliability-Based Geotechnical Design Method Using the Gaussian Process Regression–Based Differential Evolution Algorithm by Kai Wen, Zemin Kuang, Wei Zeng, Sanyou Zeng, Yue Qiu

“…A fundamental challenge in reliability-based geotechnical design is optimizing cost-effectiveness while adhering to a predefined failure probability target. …”
Get full text