Voltage Waveform and Voltage Boost Ratio of Quasi Z Source DC Converters by Sheng Qu

“…In order to optimize the voltage waveforms of quasi Z source converters and investigate their effects on voltage boost ratio, the LTspice software is used to conduct a simulation study on quasi Z source converters after theoretical analysis. …”
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Voltage unbalance assessment in a distribution system incorporated with renewable‐based sources and electric vehicles in an uncertain environment by Nandini K. K., Jayalakshmi N. Sabhahit, Vinay Kumar Jadoun

“…The proposed problem is solved using two different optimization methods i.e., a modified version of JAYA and whale optimization algorithm (WOA) using MATLAB software. …”
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Multi-Objective Robustness of Integrated Energy System Considering Source-Load Uncertainty by LI Jianlin, ZHANG Zedong, LIANG Ce, ZENG Fei

“…Therefore, a multi-objective two-stage robust optimization method is proposed, taking into account the source-load uncertainty. …”
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Pollution Source Detection With Low‐Cost Low‐Accuracy Sensors Through Coupling Forward Data Assimilation and Inverse Optimization by Chi Zhang, Zhe Zhu, Yu Li, Erhu Du, Yan Sun, Zhihong Liu

“…This study aims to develop a novel PSD method to use low‐accuracy sensor data, namely, the method of coupled forward data Assimilation and inverse Optimization in PSD (A&O‐PSD). …”
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Energy Storage Configuration Optimization of a Wind–Solar–Thermal Complementary Energy System, Considering Source-Load Uncertainty by Guangxiu Yu, Ping Zhou, Zhenzhong Zhao, Yiheng Liang, Weijun Wang

“…To address this insufficiency, this study proposes an optimal energy storage configuration method considering source-load uncertainties. …”
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Optimization of Bioactive Compound Extraction from Rose Myrtle Fruit (Rhodomyrtus tomentosa, (W.Ait), Myrtaceae) as the Antioxidant Source by Titik Ismandari, Sri Kumalaningsih, Susinggih Wijana, Siti Asma’ul Mustaniroh

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Inertia Optimization Control Model of AC/DC Sending-End System Based on Multi-source Energy Storage Coordination by Song XIANG, Peng SU, Jian WU, Xin LIU, Jitao MA

“…To address the low inertia level of AC/DC sending-end systems with high-proportion new energy access, this paper proposes an optimal control method for the inertia of such systems based on multi-source energy storage coordination. …”
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Multi-Scenario Stochastic Optimal Scheduling for Power Systems With Source-Load Matching Based on Pseudo-Inverse Laguerre Polynomials by Jiahao Ye, Lirong Xie, Lan Ma, Yifan Bian, Chuanshi Cui

“…In the optimization scheduling of power systems containing renewable energy, to ensure that the scheduling results have higher security and better economy, this study proposes a multi-objective forecasting, scenario generation, and decision scheduling integrated stochastic optimal scheduling method. …”
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Optimizing infant neuroimaging methods to understand the neurodevelopmental impacts of early nutrition and feeding by Claudia A. Carreno, Megan E. Evans, Blakely K. Lockhart, Oziomachukwu Chinaka, Benjamin Katz, Martha Ann Bell, Brittany R. Howell

“…We also discuss current challenges, as well as the scientific and logistical limitations of each method. Once protocols have been optimized, these methods will provide the requisite insight into the underlying mechanisms of nutritional and feeding impacts on neurodevelopment, providing the missing piece in the field’s efforts to understand this essential and ubiquitous part of early life.…”
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Dynamic gating-enhanced deep learning model with multi-source remote sensing synergy for optimizing wheat yield estimation by Jian Li, Jian Li, Junrui Kang, Junrui Kang, Jian Lu, Jian Lu, Hongkun Fu, Hongkun Fu, Zheng Li, Zheng Li, Baoqi Liu, Xinglei Lin, Xinglei Lin, Jiawei Zhao, Hengxu Guan, He Liu, Zhihan Liu

“…This study introduces the Spatio–Temporal Fusion Mixture of Experts (STF-MoE) model, an innovative deep learning framework built upon an LSTM-Transformer architecture.MethodsThe STF-MoE model incorporates a heterogeneous Mixture of Experts (MoE) mechanism with an adaptive gating network. …”
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A brief comparison of algorithms and methods for optimization of electric vehicles charging strategies by Arpita Bharti, Rajeev Kumar Chauhan

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Research methods of car body design optimizing for improving vehicle vibroacoustic performances by Batizi V.M., Likhachev D.S.

“…The need to improve vibration protection systems, to conduct vibroacoustic analysis and develop new methods for optimizing vehicle vibrations as a whole is a modern and urgent task for the automotive industry.In the research work, we investigated vibration and noise problems associated with the integration of the transmission of the vehicle body, as defined methods to improve vibration isolation properties of the vehicle by optimizing vehicle body stiffness characteristics.The practical significance of the work is to identify recommendations for reducing the vibration loads transmitted to the driver, which will make it possible to make optimal technical decisions in the early stages of the development of the vehicle body.Using engineering analysis or combined methodologies, the process for optimizing the vibroacoustic characteristics of the vehicle should be based on a systematic approach and evaluate the appropriate compromise between a high level of safety, weight reduction, ensuring vehicle fuel economy and customer requirements such as controllability and vibroacoustic comfort.In the article, based on the analysis of literary sources, vibroacoustic phenomena associated with various transmission components and subsystems are identified. …”
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Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method by Suwei Wang, Lile Wang, Subo Dong

“…Here, we develop the Twinkle code, an efficient and robust binary-lens modeling software suite optimized for heterogeneous computing devices, especially GPUs. …”
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Lighting Spectrum Optimization With Deep Learning for Moss Species Classification by Kenichi Ito, Pauli Falt, Markku Hauta-Kasari, Shigeki Nakauchi

“…Additionally, adequate lighting is crucial for detailed imaging in dark environments lacking ambient light. Hence, we propose a method for obtaining spectral information on moss in the forest using a deep learning model to train convolutional neural network models while optimizing a suitable light source for moss identification. …”
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Harmonic State Estimation Method Based on Bayesian Optimized Elastic Network Regression by Siqi MA, Zhong WANG

“…In order to accurately estimate the harmonic state of the power system, a harmonic state estimation method is proposed based on Bayesian optimization elastic network regression. …”
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Integrating Mobile Devices and Wearable Technology for Optimal Sleep Conditions by You-Kwang Wang, Chien-Yu Chen

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Optimal Operation Method for Microgrid with Wind/PV/Diesel Generator/Battery and Desalination by Qingfeng Tang, Nian Liu, Jianhua Zhang

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AUTONOMOUS POWER SUPPLY SYSTEMS WITH RENEWABLE SOURCES OF ENERGY AND SMART GRID by L. M. Chetoshnikova, N. I. Smolentsev, S. A. Chetoshnikov, G. V. Gusarov

“…Especially effective in this direction will be the construction of autonomous systems using renewable energy sources and local smart grids. The coordinated work of all elements of systems and optimal control of energy flows is solved by mathematical modeling methods.…”
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The impact of urban parks on the thermal environment of built-up areas and an optimization method. by Yujun Yang, Yuheng Lv, Dian Zhou

“…This manuscript takes Xi'an as the research area, using remote sensing data as the data source and combining field surveys, to explore the cooling characteristics of the cold island effect in the urban built-up area. …”
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Multi energy dynamic soaring trajectory optimization method based on reinforcement learning by ZHANG Yunfei, WANG Honglun, ZHANG Menghua, GONG Yinan

“…The experiments initially validate the approach through simulation of two classic modes of dynamic soaring, followed by Monte Carlo simulations considering multiple energy sources. The results indicate that the dynamic soaring trajectory optimization method based on deep reinforcement learning achieves energy acquisition comparable to optimal outcomes within a single soaring cycle, with a 91% reduction in real-time inference decision time. …”
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