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Assessing agricultural salt-affected land using digital soil mapping and hybridized random forests

GEODERMA 2021年 385卷 114858-114858页

作者： Nabiollahi, Kamal Taghizadeh-Mehrjardi, Ruhollah Shahabi, Aram Heung, Brandon Amirian-Chakan, Alireza Davari, Masoud Scholten, Thomas Univ Kurdistan Fac Agr Dept Soil Sci & Engn Sanandaj Iran Ardakan Univ Fac Agr & Nat Resources Ardakan Iran Univ Tubingen Dept Geosci Soil Sci & Geomorphol Tubingen Germany Dalhousie Univ Fac Agr Dept Plant Food & Environm Sci Halifax NS Canada Lorestan Univ Dept Soil Sci Khorramabad *** Iran Univ Tubingen DFG Cluster Excellence Machine Learning Tubingen Germany Univ Tubingen CRC Resource Cultures 1070 Gartenstr 29 Tubingen Germany

Salinization and alkalization are predominant environmental problem world-wide which their accurate assessment is essential for determining appropriate ways to deal with land degradation, for better soil and crop management. In the current research, a combination of random forests and covariate data were used to assess spatial variability of soil salinity and sodicity in 436 km(2) agricultural salt-affected land in Kurdistan Province, Iran. Using the conditioned Latin hypercube sampling method, 295 soil samples were sampled across the study area, and then soil reaction (pH), electrical conductivity (EC), and sodium adsorption ratio (SAR) were measured. Covariate data including terrain attributes, remotely-sensed data, groundwater table, and categorical maps were acquired. Random forest (RF) models were used to predict the spatial distribution of pH, EC, and SAR by making a relationship between soil data and covariates. Furthermore, three optimization algorithms (particle swarm optimization-PSO, genetic algorithm-GA, and bat algorithm-BAT) were used to explore if the hybridized RF works better than the standard RF. Results of 10-fold cross-validation with 100 replications indicated that the accuracy of RF PSO was higher for predicting pH (RMSE = 0.52 and R-2 = 0.67), EC (RMSE = 2.32 dSm(-1) and R-2 = 0.57), and SAR (RMSE = 8.98 and R-2 = 0.54, respectively) in comparison to the other implemented models. Furthermore, the results disclosed that the most important covariates to predict pH, EC, and SAR were groundwater table, categorical maps, salinity index, and multi-resolution ridge top flatness. Besides, the results indicated that the mean values for pH, EC, and SAR in lowland and bare land were significantly different from the other physiographic units and land uses, respectively. Importantly, the classified map of salt-affected soils highlighted areas with a high risk of exceeding critical threshold values of pH, EC, and SAR, which is located in the center of the s

关键词： Digital soil mapping Random forest optimization algorithms Soil salinity Soil sodicity

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A Comprehensive Review of Sizing and Energy Management Strategies for Optimal Planning of Microgrids with PV and Other Renewable Integration

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APPLIED SCIENCES-BASEL 2024年第22期14卷 10479页

作者： Kassab, Fadi Agha Rodriguez, Rusber Celik, Berk Locment, Fabrice Sechilariu, Manuela Univ Technol Compiegne Ctr Pierre Guillaumat CS 60203 F-60319 Compiegne France

This article comprehensively reviews strategies for optimal microgrid planning, focusing on integrating renewable energy sources. The study explores heuristic, mathematical, and hybrid methods for microgrid sizing and optimization-based energy management approaches, addressing the need for detailed energy planning and seamless integration between these stages. Key findings emphasize the importance of optimal sizing to minimize costs and reduce carbon dioxide (CO2) emissions while ensuring system reliability. In a pedagogical manner, this review highlights the integrated methodologies that simultaneously address sizing and energy management and the potential of emerging technologies, such as smart grids and electric vehicles, to enhance energy efficiency and sustainability. This study outlines the importance of accurate load modeling and carefully selecting models for renewable energy sources and energy storage systems, including degradation models, to achieve long-term operational efficiency and sustainability in microgrid design and operation. Future research should focus on developing multi-objective optimization techniques and incorporating cutting-edge technologies for improved microgrid planning and operation.

关键词： microgrid renewable energy integration energy management optimal sizing hybrid methodologies optimization algorithms sustainability smart grids

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Advanced Optical Imaging Based on Metasurfaces

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ADVANCED OPTICAL MATERIALS 2024年第6期12卷

作者： Zou, Xiujuan Lin, Ruoyu Fu, Yunlai Gong, Guangxing Zhou, Xuxi Wang, Shuming Zhu, Shining Wang, Zhenlin Nanjing Univ Sch Phys Natl Lab Solid State Microstruct Nanjing 210093 Peoples R China Nanjing Univ Key Lab Intelligent Opt Sensing & Manipulat Minist Educ Nanjing 210093 Peoples R China Collaborat Innovat Ctr Adv Microstruct Nanjing 210093 Peoples R China

Recently, metasurfaces have arisen as next-generation optics with various merits, such as being ultrathin and lightweight with multi-function integration. Numerous applications of metasurfaces have been demonstrated up to now, including wavefront shaping, optical imaging, hologram display, structured light generation, polarization detection, and so on. Among them, optical imaging components and techniques have been substantially promoted with the advent of metasurfaces due to their superior spatial modulation properties over electromagnetic waves. Here, the forward and reverse design approaches of metasurface and recent advances in various imaging applications based on them are reviewed. Due to the ability of arbitrary wavefront encoding, metasurfaces have been widely applied to numerous imaging applications, including diffraction-limited imaging with aberration correction, polarization-related imaging, high-resolution spectral imaging, three-dimentional (3D) imaging, and even algorithm-assisted imaging, etc. Optical imaging applications combined with novel metasurfaces can make breakthroughs with the development of nanofabrication technologies and the improvement of computer algorithms.

关键词： imaging applications metasurfaces optimization algorithms phase-modulation

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Shapley Additive Explanations of Multigeometrical Variable Coupling Effect in Transonic Compressor

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JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME 2022年第4期144卷 041015-041015页

作者： Wang, Junying He, Xiao Wang, Baotong Zheng, Xinqian Tsinghua Univ Turbomachinery Lab State Key Lab Automot Safely & Energy Beijing 100084 Peoples R China Imperial Coll London Dept Mech Engn London SW7 2AZ England Tsinghua Univ Inst Aero Engine Beijing 100084 Peoples R China Tsinghua Univ Dept Aerodynam & Thermodynam Inst Aero Engine Beijing 100084 Peoples R China

optimization algorithms in the compressor detailed design stage generate big data of geometries and corresponding performances, but these data are often not exploited efficiently to unveil hidden compressor design guidance. In this work, the Shapley additive explanations (SHAP) method from game theory is proposed as an efficient methodology to extract design guidelines from databases. A database was generated when optimizing the blade features (sweep, lean, and end-bend) of Rotor 37. Based on this, a neural network is trained to predict compressor efficiency. The SHAP method is then applied to explain the neural network behavior, which provides information on the sensitivity of single geometrical variables and the coupling effect between multiple geometrical variables. Results show that the near-tip sweep and midspan lean angles are most influential on efficiency. Within the same group of variables, the adjacent variables tend to present strong positive coupling effects on efficiency. Among different groups, evident coupling effects are observed between sweep and lean and between lean and end-bend, but the coupling effect between sweep and end-bend is negligible. Flow mechanisms behind the coupling effects are discussed. For near-tip lean angles L3 and L4, the positive coupling effect is due to the change of the passage shock. For near-tip lean angle L4 and sweep angle S4, the change of detached shock leads to a negative coupling effect. The proposed data mining method based on the neural network and SHAP is promising and transferable to other turbomachinery optimization databases in the future.

关键词： optimization Blades Rotors Design Flow (Dynamics) Computational fluid dynamics Compressors optimization algorithms Artificial neural networks Data mining Databases

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Investigation on the optimized algorithm for electrostatic tomography

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REVIEW OF SCIENTIFIC INSTRUMENTS 2018年第8期89卷 085116-085116页

作者： Gao, H. M. Fan, B. Y. Min, Y. X. Chang, Qi Xian Univ Technol Sch Mech & Precis Instrument Engn 5 Jinhuanan Rd Xian 710048 Shaanxi Peoples R China

Particle charging in gas-solid two-phase flow is an important concern in many industrial processes. The technique of electrostatic tomography (EST) based on particle charging can achieve flow regime identification and infer concentration and flow rate by detecting the charged particles. Successful application of EST depends on the sensitivity map and the image reconstruction algorithm. In this paper, the effects of the sensitivity map on EST were demonstrated and a novel sensitivity map was presented. Then, optimized Tikhonov iterative algorithm (ITIK) was proposed to improve the quality of EST. The simulated results illustrate that the novel sensitivity map improves the quality of the reconstructed image of EST and the optimized ITIK has better performance in reconstructing the image of EST when compared with linearized back-projection algorithm, iterative linearized back-projection algorithm, and ITIK. Finally, the experimental studies were conducted and the simulated results were validated. The results indicate that the novel sensitivity map and the optimized algorithm can enable good applications of EST in gas-solid two-phase flow measurement. Published by AIP Publishing.

关键词： maps SENSITIVITY MAPPING Tomography Electrostatics Expressed Sequence Tags Projection algorithms optimization algorithms Ions

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Empirical Correction of Stray Light within the MERIS Oxygen A-Band Channel

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JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY 2010年第7期27卷 1185-1194页

作者： Lindstrot, Rasmus Preusker, Rene Fischer, Jurgen Free Univ Berlin Inst Weltraumwissensch D-12165 Berlin Germany

Spaceborne spectrometers like the Medium Resolution Imaging Spectrometer (MERIS) on board the Environmental Satellite (Envisat) are widely used for the remote sensing of atmospheric and oceanic properties and make an important contribution to the monitoring of the earth's atmosphere system To enable retrievals with high accuracy, the spectral and radiometric properties of the instruments have to be characterized with high precision One of the main sources of radiometric errors is stray light caused by multiple reflections and scattering at the optical elements within the instruments If not corrected for properly, the stray light-induced offsets of measured intensity can lead to significant errors in the derived parameters The effect of stray light is particularly momentous in the case of measurements inside strong absorption bands like the oxygen A band at 076 mu m or the rho sigma tau absorption band of water vapor around 09 mu m For example, the retrieval of surface and cloud-top pressure from MERIS measurements in the O-2 A hand can be biased because of an insufficient correct ion of stray light in the operational processing chain To correct for the residual stray light influence after the operational stray light correction in the O-2 A-band channel of MER IS. an empirical stray light correction of the measured radiance at 0 76 mu m has been developed based on optimizing the coefficients of a simple brightness-dependent stray light model The optimal model coefficients were found by adjusting the retrievals of surface and cloud-top pressure to accurate reference data for several selected scenes To account for the limited accuracy of the MERIS spectral calibration. the center wavelength of the O-2 A-band channel was additionally adjusted within a +/- 0 1-nm tolerance range The correction was tested on a variety of clear and cloudy scenes at different locations by applying the surface and cloud-top pressure retrieval algorithms to data recorded over the whole lifeti

关键词： Clouds Accuracy Cameras Remote sensing optimization algorithms Light

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A deep learning method for grid-free localization and quantification of sound sources

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JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2019年第3期146卷 EL225-EL231页

作者： Kujawski, Adam Herold, Gert Sarradj, Ennes Tech Univ Berlin Einsteinufer 25 D-10587 Berlin Germany

In this contribution it is examined whether the use of deep neural networks can lead to an accurate characterization of single point sources from microphone array data. Based on conventional beamforming maps, the proposed method aims at estimating the source coordinates and the strength. The residual network architecture, a well-established model in the field of image recognition, is successfully applied to this task. The investigation reveals a method that fast and accurately renders the position and strength of an unknown source. Moreover, the accuracy of the position estimation is higher than the grid resolution of the beamforming map.

关键词： Acoustical properties Acoustic beamforming Acoustic signal processing Microphone array Artificial intelligence optimization algorithms Acoustic noise Artificial neural networks Photoacoustic imaging Functions and mappings

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The Detection and Significance of Diurnal Pressure and Potential Vorticity Anomalies East of the Rockies

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JOURNAL OF THE ATMOSPHERIC SCIENCES 2010年第9期67卷 2734-2751页

作者： Li, Yanping Smith, Ronald B. Yale Univ Dept Geol & Geophys Kline Geol Lab New Haven CT 06511 USA

Harmonic analysis of pressure, temperature, and precipitation data from 1000 Automated Surface Observing System (ASOS) stations reveals a mix of stationary and east west moving disturbances east of the Rockies. optimization of the pressure data using a "temperature-based tide assumption" separates a strong sun-following continentally enhanced tide from a smaller eastward-propagating wave (EPW). The latter signal moves at a similar speed to the previously discovered eastward-moving precipitation systems. Analysis of ASOS summer precipitation data confirms eastward propagation, but east of 90 degrees W it shows nonpropagating diurnal convection at a fixed local time (i.e., 1800 LST). Analysis of winter days still finds the EPW, suggesting that it is the cause and not the result of the propagating precipitation. A possible mechanism for the EPW is developed from the linear Bousinesq equations with heating and wind shear. Solutions show eastward-moving diurnal pulses of potential vorticity (PV) generated by imposed heating over the Rockies. Because of the background shear, these pulses produce vertical motion in the lower troposphere. The PV hypothesis for precipitation propagation was tested with North American Regional Reanalysis (NARR) data. Diurnal drifting thermal and PV anomalies are clearly found near the 500- and 600-hPa levels in both winter and summer. In winter, the PV signal is weaker, moves faster, and does not influence precipitation. The existence of the winter PV signal again suggests that it is the cause, not the effect, of summer propagating precipitation.

关键词： Meteorology Atmosphere Wind Harmonic analysis optimization algorithms Atmospheric sciences

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Optimal Design of Adaptive Laminated Beam Using Layerwise Finite Element

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JOURNAL OF SENSORS 2011年第unknown期2011卷 240341-1-240341-8页

作者： Zabihollah, Abolghassem Zareie, Shahin Sharif Univ Technol Kish Isl Iran

First, an efficient and accurate finite element model for smart composite beams is presented. The developed model is based on layerwise theory and includes the electromechanical coupling effects. Then, an efficient design optimization algorithm is developed which combines the layerwise finite element analysis model for the smart laminated beam, sensitivity analysis based on analytical gradients and sequential quadratic programming (SQP). Optimal size/location of sensors/actuators is determined for dynamic displacement measurement purposes and for vibration control applications. For static and eigenvalue problems, the objective is to minimize the mass of the beam under various constraints including interlaminar stresses, displacements, and frequencies. For transient vibration problems, the objective is the minimization of the actuation control effort to suppress the vibration in a controlled manner. Illustrative examples are provided to validate the formulation and to demonstrate the capabilities of the present methodology.

关键词： optimization algorithms displacements laminated beams composite beams Optimal design vibration control

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Prediction models of bit errors for NAND flash memory using 200 days of measured data

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REVIEW OF SCIENTIFIC INSTRUMENTS 2019年第6期90卷 064702-064702页

作者： Wei, Debao Qiao, Liyan Chen, Xiaoyu Feng, Hua Peng, Xiyuan Harbin Inst Technol Sch Elect & Informat Engn Harbin 150080 Heilongjiang Peoples R China

NAND flash memory, with its excellent storage performance, has become a leader in storage media for scientific instruments. With improvements in the manufacturing technique, its reliability is decreasing. Thus, methods for improving the storage reliability of scientific instruments has become a major topic. If a method to effectively evaluate NAND flash error distribution is found, it will provide significant guidance for error correction codes and the wear equalization algorithm to improve the performance of NAND flash memory. It will also be a good method to predict the flash memory life. Based on data measured over 200 days from an experimental platform for the NAND flash, in this study, the polynomial fitting method, an artificial neural network, and a support vector regression were adopted to build a NAND flash bit errors prediction model, and efficacies of the methods are compared. The simulation results show that the different evaluation models have their own advantages in different situations.

关键词： Flash memory optimization algorithms Statistical analysis Regression analysis Artificial neural networks Electrical properties and parameters

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