Utilizing Enhanced Particle Swarm Optimization for Feature Selection in Gender-Emotion Detection From English Speech Signals by Ammar Amjad, Li-Chia Tai, Hsien-Tsung Chang

“…The gender-specific DGA-EBPSO algorithm incorporates a hybrid mutation strategy to improve feature selection efficiency and considers gender-based variations in emotional expression. …”
Get full text

Unboxing Tree ensembles for interpretability: A hierarchical visualization tool and a multivariate optimal re-built tree by Giulia Di Teodoro, Marta Monaci, Laura Palagi

“…The interpretability of models has become a crucial issue in Machine Learning because of algorithmic decisions' growing impact on real-world applications. …”
Get full text

Optimized actuator design for flapping-wing robots: A multi-objective approach to mimic natural flapping dynamics by Peiqi Li, Zhiwei Ai, Mufan Zhang

“…An optimized actuator for a flapping-wing robot was developed using detailed geometric and physical models to more closely mimic natural flapping dynamics. …”
Get full text

Optimizing guest experience in smart hospitality: Integrated fuzzy-AHP and machine learning for centralized hotel operations with IoT by Sinan Andan Diwan

Get full text

Scientific planning of dynamic crops in complex agricultural landscapes based on adaptive optimization hybrid SA-GA method by Changlong Li, Zengye Su, Yudan Nie, Zhiyi Ye, Jinyi Li, Jing Wang, Zicong Yang, Xuxin Li, Weijian Zeng, Yanjian Chen

“…This framework is underpinned by a sophisticated model integrating advanced monitoring systems with a Hybrid Simulated Annealing Genetic Algorithm (H-SAGA), further enhanced by neural network-driven real-time predictions. …”
Get full text

Time-delayed vibration control and parameter optimization of semi-active vehicle suspension designed for random road excitation by Yong Guo, Yong-Jing Li, Yan-Bo Wei

“…Firstly, the optimal values of time-delayed feedback control parameters are derived through an optimization algorithm based on “equivalent harmonic excitation.” …”
Get full text

Novel Gain-Optimized Two-Step Fusion Filtering Method for Ranging-Based Localization Using Predicted Residuals by Bo Chang, Xinrong Zhang, Na Sun, Hao Ni

Get full text

Research on low carbon welding scheduling based on production process by Rong Hua Meng, Zan Yang Wang, Wen Hui Zeng, Feng Guan, Ding Kun Lei, Zheng Jia Wu, Shao Hua Deng

“…Then, an improved Grey Wolf Optimizer (IGWO) with three strategies is designed to solve this multi-objective problem. …”
Get full text

Robust Optimal Control for a Microbial Batch Culture Processes: Incorporating Free Terminal Time and Sensitivity Analysis by Yang Qi, Zheng Shijin, Xie Suzhen, Feng Enmin

“…Subsequently, we develop an improved particle swarm optimization algorithm to solve this equivalent problem. …”
Get full text

Improving inverter efficiency for electric vehicles: Experimental validation of the neural network-based SHE technique using RT-LAB by Seyf Eddine Bechekir, Mokhtaria Jbilou, Mostefa Brahami, Fatima Zohra Boudjella, Imen Souhila Bousmaha, Mimouna Oukli, Said Nemmich

“…This approach improves inverter performance and offers new optimization possibilities for various applications, including electric vehicles. …”
Get full text

Three-dimensional localization algorithm of mobile nodes based on received signal strength indicator-angle of arrival and least-squares support-vector regression by Lieping Zhang, Huihao Peng, Jiajie He, Shenglan Zhang, Zuqiong Zhang

“…Finally, the unknown mobile nodes were localized based on least-squares support-vector regression modeling. The experimental results showed that compared with the localization algorithms without optimized ranging information or least-squares support-vector regression modeling, the algorithm proposed in this study exhibited significantly improved stability, a reduced mean localization error by more than 50%, and increased localization accuracy.…”
Get full text

A novel deep learning algorithm for real-time prediction of clinical deterioration in the emergency department for a multimodal clinical decision support system by Arom Choi, Kwanhyung Lee, Heejung Hyun, Kwang Joon Kim, Byungeun Ahn, Kyung Hyun Lee, Sangchul Hahn, So Yeon Choi, Ji Hoon Kim

“…The algorithm’s predictions, based solely on triage information, significantly outperformed traditional logistic regression models, with notable improvements in the area under the precision-recall curve (AUPRC). …”
Get full text

Tone mapping based on variational model in gradient domain by IZhi-hong X, Lan-fei ZHAO, Chi ZHANG, Zhong-min ZHANG

“…Due to the low dynamic range image which was generated by the gradient domain high dynamic range compression algorithm contain the artificial boundaries and local detail distortions,a variational model in gradient domain was proposed to improve the performance of the traditional algorithm.First of all,a variational model in gradient domain was introduced to compress dynamic range,meanwhile details and edges were preserved simultaneously.Afterwards,the rate of convergence was improved by introducing the ideology of Gibbs sampler.Eventually,the improved method was employed to obtain the optimal solution of the variational model.Experimental results demonstrate that proposed algorithm reduces the degree of artificial boundaries,meanwhile low dynamic range image represents excellent capacity of detail preservation.Moreover,the real-time performance is guaranteed by the improved steepest descent method.…”
Get full text

Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…This complex multi-million-dollar problem involves optimizing multiple parameters using computationally intensive reservoir simulations, often employing advanced algorithms such as optimization algorithms and machine/deep learning techniques to find near-optimal solutions efficiently while accounting for uncertainties and risks. …”
Get full text

Optimal energy management for multi-energy microgrids using hybrid solutions to address renewable energy source uncertainty by M. Siva Ramkumar, Jaganathan Subramani, M. Sivaramkrishnan, Arunkumar Munimathan, Goh Kah Ong Michael, Mohammad Mukhtar Alam

“…In this study, a new hybrid algorithm is used for system modelling and low-cost, optimal management of Micro Grid (MG) networked systems. …”
Get full text

Tone mapping based on variational model in gradient domain by IZhi-hong X, Lan-fei ZHAO, Chi ZHANG, Zhong-min ZHANG

“…Due to the low dynamic range image which was generated by the gradient domain high dynamic range compression algorithm contain the artificial boundaries and local detail distortions,a variational model in gradient domain was proposed to improve the performance of the traditional algorithm.First of all,a variational model in gradient domain was introduced to compress dynamic range,meanwhile details and edges were preserved simultaneously.Afterwards,the rate of convergence was improved by introducing the ideology of Gibbs sampler.Eventually,the improved method was employed to obtain the optimal solution of the variational model.Experimental results demonstrate that proposed algorithm reduces the degree of artificial boundaries,meanwhile low dynamic range image represents excellent capacity of detail preservation.Moreover,the real-time performance is guaranteed by the improved steepest descent method.…”
Get full text

CNN-LSTM optimized with SWATS for accurate state-of-charge estimation in lithium-ion batteries considering internal resistance by Zhaowei Zhang, Chen Liu, Tianyu Li, Tian Wang, Yaoyao Cui, Pengcheng Zhao

“…In addition, commonly used network optimization algorithms do not always maximize the convergence speed and performance simultaneously. …”
Get full text

Tackling the Optimal Phasor Measurement Unit Placement and Attack Detection Problems in Smart Grids by Incorporating Machine Learning by Ramzi Al-Sharawi, Abdelfatah Ali, Mostafa Shaaban, Nasser Qaddoumi, Mohamed S. Abdalzaher

“…Specifically, the k-Nearest Neighbors (KNN) model’s Brier loss is used as an objective function within the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) optimization framework to represent the FDIA detection performance. …”
Get full text

Intelligent Energy-Efficient Train Trajectory Optimization Approach Based on Supervised Reinforcement Learning for Urban Rail Transits by Guannan Li, Siu Wing Or, Ka Wing Chan

“…Second, an IETTO model is established to handle uncertain disturbances in real-time train operation and generate optimal energy-efficient train trajectories online by optimizing energy efficiency and receiving supervisory information from trajectories of pre-trained TTO models. …”
Get full text

Performance Optimization of Synchronous Reluctance Motor using Adaptive MTPA Curve Fitting with Anti-Windup Current Control by Alex V, Rammohan A

“…Conventional scalar control methods typically rely on precomputed lookup tables or iterative optimization algorithms, which introduce computational overhead and require significant memory resources. …”
Get full text