How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression by Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Judith M. Burnfield

“…This study uses Artificial Neural Networks (ANNs) and multiple linear regression (MLR) models to explore the relationship between gait dynamics and the metabolic cost. Six nonlinear metrics—Lyapunov Exponents based on Rosenstein’s algorithm (LyER), Detrended Fluctuation Analysis (DFA), the Approximate Entropy (ApEn), the correlation dimension (CD), the Sample Entropy (SpEn), and Lyapunov Exponents based on Wolf’s algorithm (LyEW)—were utilized to predict the metabolic cost during walking. …”
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Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration by Gudi V. Chandra Sekhar, Chekol Alemu

“…XGBoost achieved optimal performance with highest $$\text {AUC}$$ (0.956, 95% $$\text {CI}$$ : 0.952–0.961) and competitive clinical cost (5,496), representing 2.8% improvement over Random Forest. …”
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Optimizing Fairness and Spectral Efficiency With Shapley-Based User Prioritization in Semantic Communication by Moirangthem Tiken Singh, Adnan Arif, Rabinder Kumar Prasad, Bikramjit Choudhury, Chandan Kalita, Sikdar Md. S. Askari

“…The Shapley-based approach outperforms established methods, including the Hungarian algorithm, reinforcement learning algorithms like Deep Q-Network (DQN) and Proximal Policy Optimization (PPO), as well as conventional 4G and 5G resource allocation strategies. …”
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Comprehensive Performance-Oriented Multi-Objective Optimization of Hemispherical Resonator Structural Parameters by Xiaohao Liu, Xin Jin, Chaojiang Li, Yumeng Ma, Deshan Xu, Simin Guo

“…Subsequently, the NSGA-II algorithm is applied to perform multi-objective mapping of these parameters, achieving an optimized resonator with a 4.61% increase in the minimum frequency difference from interference modes and a substantial improvement in thermoelastic damping of approximately 70.41%. …”
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Multiobjective Cognitive Cooperative Jamming Decision-Making Method Based on Tabu Search-Artificial Bee Colony Algorithm by Fang Ye, Fei Che, Lipeng Gao

“…Most of the existing studies about jamming decision only pay attention to the jamming benefits, while ignoring the jamming cost. In addition, the conventional artificial bee colony algorithm takes too many iterations, and the improved ant colony (IAC) algorithm is easy to fall into the local optimal solution. …”
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Research on Optimization of Large-Scale Heterogeneous Combat Network Based on Graph Embedding by Xianzheng Meng, Changrong Xie, Hui Li, Guangjun Zeng, Kebin Chen

“…It has shown a 17.23% improvement in this aspect compared to HCNOF0 and a 6.89% enhancement when compared to the GE-SU-EANet algorithm, underscoring its advantages in both optimization performance and cost reduction. …”
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Contextual Regularization-Based Energy Optimization for Segmenting Breast Tumor in DCE-MRI by Priyadharshini Babu, Mythili Asaithambi, Sudhakar Mogappair Suriyakumar

“…An iterative gradient descent algorithm is engaged to minimize the energy-based cost function, obtaining stable convergence towards the optimal solution. …”
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Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization by Sumet Mehta, Fei Han, Muhammad Sohail, Bhekisipho Twala, Asad Ullah, Fasee Ullah, Arfat Ahmad Khan, Qinghua Ling

“…The analysis of high-dimensional microarray gene expression data presents critical challenges, including excessive dimensionality, increased computational burden, and sensitivity to random initialization. Traditional optimization algorithms often produce inconsistent and suboptimal results, while failing to preserve local data structures limiting both predictive accuracy and biological interpretability. …”
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Research on Multi-Objective Coordinated Planning of Distribution Networks Based on Improved Generative Adversarial Networks by Li Zhu

“…Next, a bi-level distribution network planning model considering carbon footprints is established: the upper level minimizes the annual comprehensive cost by optimizing the planning schemes of distributed generation (DG), energy storage systems (ESS), and capacitor banks (CB); the lower level minimizes operating costs, voltage deviations, and carbon emissions by formulating operation strategies under typical scenarios, considering on-load tap changers (OLTC), controllable loads, capacitor banks, energy storage, and distributed generation. …”
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Predicting compressive strength of concrete at elevated temperatures and optimizing its mixture proportions by Jinjun Xu, Han Wang, Wenjun Wu, Lang Lin, Yong Yu

“…The Cuckoo search algorithm was then employed to optimize mix designs, balancing high-temperature strength, cost and sustainability. …”
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Towards a digital twin: Digitization and model-based optimization of the innovative high-gradient magnetic separatorMendeley Data by Marko Tesanovic, Torben Bardel, Robin Karl, Sonja Berensmeier

“…Optimization results indicated a theoretical 4% productivity gain and a 3 percentage point yield improvement, while exposing critical design constraints in the HGMS chamber.These findings underscore the potential of digital twins to accelerate process optimization and reduce development costs through in-silico experimentation. …”
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Expansion of Output Spatial Extent in the Wavenumber Domain Algorithms for Near-Field 3-D MIMO Radar Imaging by Yifan Gong, Limin Zhai, Yan Jia, Yongqing Liu, Xiangkun Zhang

“…To suppress aliasing while expanding the output spatial extent, an optimization approach for the wavenumber domain algorithms is proposed. …”
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Optimizing Robotic Arm Learning: Curiosity-Driven Deep Deterministic Policy Gradient by Liu Jiarun

“…However, collecting the large- scale real-world data is costly and impractical, making simulation environments essential for optimization. …”
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Research Progress on Machine Learning Prediction of Compressive Strength of Nano-Modified Concrete by Ruyan Fan, Ankang Tian, Yikun Li, Yue Gu, Zhenhua Wei

“…However, testing nano-concrete is costly and complex because it requires control over many factors, such as nanoparticle content and dispersion. …”
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A Cooperative Generation Expansion Planning of Microgrids to Improve the Resiliency of Active Distribution Networks by Mohammad Hossein Atazadegan, Esmaeel Rokrok, Meysam Doostizadeh

“…In this case, the multi objective optimization problem, including the objective functions of total cost and environmental pollution, has been solved using fuzzy decision-making and multi-objective improved golden ratio optimization algorithm based on the Pareto front.…”
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Smart UAV-assisted rose growth monitoring with improved YOLOv10 and Mamba restoration techniques by Fan Zhao, Zhiyan Ren, Jiaqi Wang, Qingyang Wu, Dianhan Xi, Xinlei Shao, Yongying Liu, Yijia Chen, Katsunori Mizuno

“…We introduced MambaIR, a novel SRR algorithm based on selective state-space models, which significantly outperforms existing methods in enhancing low-resolution UAV imagery (PSNR: 28.34 dB, SSIM: 77.07 %). …”
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Clean energy supply chain optimization: Steady-state natural gas transportation by Zhongfu Liu, Shuiying Xu, Shihao Zhao, Yuewen Li, Meiling Zhou, Shuosen Li, Fei Meng

“…The objective is to minimize pipeline transportation costs and energy consumption, achieving optimization of the steady-state operation of the natural gas pipeline system. …”
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Rejection-Free Monte Carlo Simulation of QUBO and Lechner–Hauke–Zoller Optimization Problems by Yoshihiro Nambu

“…Landscapes of success probabilities of finding the globally optimal solution as well as feasible solutions were evaluated as a function of a set of hyper-parameters used to characterize the weights of cost and penalty functions. …”
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Low-carbon economic dispatch based on improved ISODATA scenario reduction for wind power in IES by Yuangen HUANG, Xingyu LIU, Tianran LI, Zhenya JI, Wei XU

“…Then, an integrated energy model is established and it optimized using an improved stepwise carbon trading and power to gas and carbon capture system (P2G-CCS) coupling model. …”
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Optimal scheduling of BIES with multi-energy flow coupling based on deep RL by XIA Xuhua, YANG Jiandi, SHI Yongtao

“…Results demonstrate that， compared to similar methods， the proposed method achieves faster convergence， more stable optimization effects， and effectively reduces both daily energy costs and carbon emission costs in IES operations.…”
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