Adaptive Scheduling and Routing Scheme for Delay Guarantee in Wireless Sensor Networks by Yan Sun, Cong Chen, Hong Luo

“…Motivated by this, we propose an adaptive scheduling and routing scheme for guaranteeing dynamic end-to-end delay requirement while minimizing the energy consumption. First of all, we utilize an optimal wake-up scheduling algorithm to achieve the initial wake-up schedules and routes and design an adaptive adjustment algorithm. …”
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Enhancing Resilience and Efficiency in Power System: A Five-Level Dynamic Planning Model by Mahnaz Rezaei, Mohammad Tolou Askari, Meysam Amirahmadi, Vahid Ghods

“…The fifth level deals with transmission expansion planning to boost resilience, and the capability of transmission switching is regarded as a low-cost correction factor. The first level optimizes energy hub according to the differential evolutionary algorithm, but the next four levels employ a robust symphony orchestra search algorithm. …”
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Utilizing UAVs in Wireless Networks: Advantages, Challenges, Objectives, and Solution Methods by Mohammad Javad Sobouti, Amirhossein Mohajerzadeh, Haitham Y. Adarbah, Zahra Rahimi, Hamed Ahmadi

“…Additionally, we discuss the main methods and algorithms employed for UAV placement and trajectory optimization. …”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Eventually, the walrus optimization algorithm (WOA) is used for hyperparameter tuning to improve the parameters of the SSAE approach and achieve optimal performance. …”
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The Current Development Status of Agricultural Machinery Chassis in Hilly and Mountainous Regions by Renkai Ding, Xiangyuan Qi, Xuwen Chen, Yixin Mei, Anze Li

“…In alignment with China’s “Dual Carbon” strategy and the unique operational requirements of hilly–mountainous areas (such as high gradients, uneven terrain, and small field sizes), this study proposes three key technological directions for the development of intelligent agricultural machinery chassis: (1) Multi-mode traveling mechanism design: Aimed at improving terrain traversability (ground clearance ≥400 mm, obstacle-crossing height ≥ 250 mm) and traction stability (slip ratio < 15%) across diverse landscapes. (2) Coordinated control algorithm optimization: Designed to ensure stable torque output (fluctuation rate < ±10%) and maintain gradient operation efficiency (e.g., less than 15% efficiency loss on 25° slopes) through power–drive synergy while also optimizing energy management strategies. (3) Intelligent perception system integration: Facilitating high-precision adaptive leveling (accuracy ± 0.5°, response time < 3 s) and enabling terrain-adaptive mechanism optimization to enhance platform stability and operational safety. …”
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Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

“…Bayesian optimization fine-tuned each model's hyperparameters to identify the optimal model-FS combination. …”
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Klasifikasi Kebutuhan Jumlah Produk Makanan Customer Menggunakan K-Means Clustering dengan Optimasi Pusat Awal Cluster Algoritma Genetika by Yudi Istianto, Shofwatul 'Uyun

“…This study tries to apply data mining to classify the number of customer needs for food products using k-means clustering with optimization initial cluster center genetic algorithm. …”
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A novel pulse-current waveform circuit for low-energy consumption and low-noise transcranial magnetic stimulation by Xinhua Tan, Ao Guo, Jiasheng Tian, Yingwei Li, Yingwei Li, Jian Shi

“…This study proposes a novel, non-resonant, high-frequency switching design controlled by high-frequency pulse-width modulation (PWM) voltage excitation to achieve ideal pulse-current waveforms that minimize both clicking noise and heat generation from the TMS coil.MethodFirst, a particle swarm optimization algorithm was used to optimize the pulse-current waveform, minimizing both the resistance loss and clicking noise (vibration energy) generated by the TMS coils. …”
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Local Alignment of DNA Sequence Based on Deep Reinforcement Learning by Yong-Joon Song, Dong-Ho Cho

“…This paper proposes a DQN x-drop algorithm that performs local alignment without human intervention by combining the x-drop algorithm with this DQNalign algorithm. …”
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Numerical Prediction of Solid Particle Erosion in Jet Pumps Based on a Calibrated Model by Xuanchen Wan, Mengxue Dong, Maosen Xu, Chuanhao Fan, Jiegang Mou, Shuai Han

“…The CFD-DEM method was used to simulate the solid–liquid two-phase flow in the jet pump, comparing six erosion models for predicting erosion rates. The Grey Wolf Optimization algorithm was applied to calibrate model coefficients. …”
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Collaborative Relay Beamforming Based on Minimum Power for M2M Devices in Multicell Systems by Xiaoning Zhang, Da Wang, Lin Bai, Chen Chen

“…The main contribution of this paper is that we propose an iterative algorithm to jointly optimize the BS and relay beamforming weights with minimizing the BS and relay power under the receive SINR constraints in the perfect channel state information (CSI). …”
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Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

“…Specifically, we frame the problem as an optimization process with the objective of minimizing a weighted loss function that balances cross-domain discrepancies and sample complexity. …”
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Phase Error Correction in Sparse Linear MIMO Radar Based on the Equivalent Phase Center Principle by Wenyuan Shao, Jianmin Hu, Yicai Ji, Jun Pan, Guangyou Fang

“…Multiple-input multiple-output (MIMO) technology is widely used in the field of radar imaging. Array sparse optimization reduces the hardware cost of MIMO radar, while virtual aperture and the equivalent phase center (EPC) principle simplify the radar signal model and reduce the computation and complexity of imaging algorithms. …”
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Urban Land-use Features Mapping from LiDAR and Remote Sensing Images using Visual Transformer Network Model by Q. Yuan

“…LiDAR has relatively accurate three-dimensional spatial information, while remote sensing image has rich spectral information. …”
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Renal failure in patients with hematological malignancies (literature review) by E. G. Gromova

“…The main reasons for the renal failure development in hematological cancer patients and syndromes that prevent adequate antitumor therapy are considered. Diagnostic algorithm optimization and supportive intensive care of acute renal failure is the key to the successful application of highly effective modern protocols of drug anticancer treatment.A special group is represented by patients suffering from monoclonal gammopathies with acute renal injury and hyperproduction of immunoglobulins free light chains. …”
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An Improved Low-Bit-Rate Image Compression Framework Based on Semantic-Aware Model and Neighborhood Attention by Chengbin Zeng, Liang Zhang

“…In addition, our proposed algorithm effectively mitigates distortions in facial and textual regions while preserving the structural integrity and visual fidelity. …”
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Numerical Solution of the Inverse Thermoacoustics Problem Using QFT and Gradient Method by Syrym E. Kasenov, Aigerim M. Tleulesova, Almas N. Temirbekov, Zholaman M. Bektemessov, Rysbike A. Asanova

“…The inverse problem was reduced to an optimization problem, where the objective function was minimized using gradient methods, including the accelerated Nesterov algorithm. …”
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A Data Resource Trading Price Prediction Method Based on Improved LightGBM Ensemble Model by Wan Nie, Bingliang Shen, Desheng Li

“…To address the key challenges of limited practical application, high implementation difficulty, and poor generalization capability in existing theoretical models for data resource pricing, this study employs generative adversarial network (GAN) to augment the dataset and constructs a DRV-LightGBM model based on a Bayesian parameter optimization algorithm that maximizes the coefficient of determination (<inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) to predict data resource transaction prices and provide post-hoc explanations for the prediction model. …”
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Improved deep learning model for accurate energy demand prediction and conservation in electric vehicles integrated with cognitive radio networks by V. Niranjani, Anandakumar Haldorai

“…To overcome this issue, this paper proposed a model of Empirical Mode Decomposition with CNN and optimized with Seagull Optimization Algorithm (EMD-CNN-SOA). …”
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Experimental and numerical investigation on thermal performance of enhanced geothermal system: A case study of Guanzhong basin by Guoyao Jin, Yuxiang Zhao, Ye Min, Xiao Zhang, Chao Jiang, Zijing Tan

“…A multi-objective genetic algorithm correlates operational variables with extraction efficiency, providing a quantitative framework for optimization. …”
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