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A study on agriculture engineering implements using machine learning

Materials Today: Proceedings 2022年 62卷 4996-5002页

作者： Sakthipriya, Dhinakaran Chandrakumar, Thangavel Department of Applied Mathematics & Computational Science Thiagarajar College of Engineering Tamil Nadu Madurai 625015 India

India's primary source of income is agriculture. Farmers in India have differing perspectives on how to integrate technology into their farming operations. However, farmers lack the knowledge necessary to put technology into practice, even though crop yield productivity is improving. We performed a literature survey to get the suggestion of what types of agriculture engineering machinery had been employed to boost up crop production output. After some literature survey, this research work followed to implement machine learning techniques to provide better advice to farmers to use the agriculture engineering machinery to minimize manpower and boost crop productivity. According to this additional analysis, clustering is the most widely used machine learning technique to solve problems in agriculture fields. Regarding the execution time, k-means performed well for other clustering techniques for small and large datasets. In this research initiates three thousands of combined data in agri-machinery in various districts, this selective data should be assured the preferable results with the help of k-means clustering for an crops highest yield production. This research work fully engaged with k-means techniques to deeply analysis in the Agri machinery benefits for south region districts and it provides the strongly recommended machinery's knowledge to farmers to implement the farming works effectively. In this research that statistical ranges are predicted what type of machinery's gives good results for crop development in south TamilNadu farming land in the district wise. The goal of this study was to evaluate statistical ranges of agriculture types of machinery in south TamilNadu districts. This proposed effort aims to provide a better proposal for achieving a suitable level of crop output with the use of more agricultural technology. © 2022

关键词： Crops

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Predator Prey Scavenger Model using Holling’s Functional Response of Type III and Physics-Informed Deep Neural Networks

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International Journal of applied and computational mathematics 2025年第2期11卷 1-32页

作者： Panchal, Aneesh Beniwal, Kirti Kumar, Vivek Department of Computational and Data Sciences Indian Institute of Science Karnataka Bangalore 560012 India Department of Applied Mathematics Delhi Technological University Delhi New Delhi 110042 India

Nonlinear mathematical models introduce the relation between various physical and biological interactions present in nature. One of the most famous models is the Lotka–Volterra model which defined the interaction between predator and prey species present in nature. However, predators, scavengers, and prey populations coexist in a natural system where scavengers can additionally rely on the dead bodies of predators present in the system. Keeping this in mind, the formulation and simulation of the predator–prey scavenger model is introduced in this paper. For the predation response, respective prey species are assumed to have Holling’s functional response of type III. The proposed model is tested for various simulations and is found to be showing satisfactory results in different scenarios. After simulations, the American forest dataset is taken for parameter estimation which imitates the real-world case. For parameter estimation, a physics-informed deep neural network is used with the Adam backpropagation method which prevents the avalanche effect in trainable parameters updation. For neural networks, mean square error and physics-informed informed error are considered. After the neural network, the hence-found parameters are fine-tuned using the Broyden–Fletcher–Goldfarb–Shanno algorithm. Finally, the hence-found parameters using a natural dataset are tested for stability using Jacobian stability analysis. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2025.

关键词： Broyden–Fletcher–Goldfarb–Shanno optimization Physics-informed deep neural network Predator prey scavenger model Stability analysis

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A folding preprocess for the max k-cut problem

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Optimization Letters 2025年第5期19卷 899-917页

作者： Fakhimi, Ramin Validi, Hamidreza Hicks, Illya V. Terlaky, Tamás Zuluaga, Luis F. Department of Industrial and Systems Engineering Lehigh University Bethlehem United States Department of Industrial Manufacturing & Systems Engineering Texas Tech University Lubbock United States Department of Computational Applied Mathematics & Operations Research Rice University Houston United States

Given graph G=(V,E) with vertex set V and edge set E, the max k-cut problem seeks to partition the vertex set V into at most k subsets that maximize the weight (number) of edges with endpoints in different parts. This paper proposes a graph folding procedure (i.e., a procedure that reduces the number of the vertices and edges of graph G) for the weighted max k-cut problem that may help reduce the problem’s dimensionality. While our theoretical results hold for any k≥2, our computational results show the effectiveness of the proposed preprocess only for k=2 and on two sets of instances. Furthermore, we observe that the preprocess improves the performance of a MIP solver on a set of large-scale instances of the max cut problem. © The Author(s) 2025.

关键词： Network theory (graphs)

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Nearly optimal state preparation for quantum simulations of lattice gauge theories

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Physical Review A 2024年第1期110卷 012455-012455页

作者： Christopher F. Kane Niladri Gomes Michael Kreshchuk Department of Physics Applied Mathematics and Computational Research Division Physics Division

We present several improvements to the recently developed ground-state preparation algorithm based on the quantum eigenvalue transformation for unitary matrices (QETU), apply this algorithm to a lattice formulation of U(1) gauge theory in (2+1) dimensions, as well as propose an alternative application of QETU, a highly efficient preparation of Gaussian distributions. The QETU technique was originally proposed as an algorithm for nearly optimal ground-state preparation and ground-state energy estimation on early fault-tolerant devices. It uses the time-evolution input model, which can potentially overcome the large overall prefactor in the asymptotic gate cost arising in similar algorithms based on the Hamiltonian input model. We present modifications to the original QETU algorithm that significantly reduce the cost for the cases of both exact and Trotterized implementation of the time evolution circuit. We use QETU to prepare the ground state of a U(1) lattice gauge theory in two spatial dimensions, explore the dependence of computational resources on the desired precision and system parameters, and discuss the applicability of our results to general lattice gauge theories. We also demonstrate how the QETU technique can be utilized for preparing Gaussian distributions and wave packets in a way which outperforms existing algorithms for as little as nq≳2–5 qubits.

关键词： Quantum algorithms Quantum simulation Lattice gauge theory

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Anomalous Thermal Transport across the Superionic Transition in Ice

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Chinese Physics Letters 2023年第11期40卷 73-77页

作者：邱荣曾启昱王涵康冬冬余晓翔戴佳钰 Department of Physics National University of Defense TechnologyChangsha 410073China Hunan Key Laboratory of Extreme Matter and Applications National University of Defense TechnologyChangsha 410073China Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China

Superionic ices with highly mobile protons within stable oxygen sub-lattices occupy an important proportion of the phase diagram of ice and widely exist in the interior of icy giants and throughout the *** the thermal transport in superionic ice is vital for the thermal evolution of icy ***,it is highly challenging due to the extreme thermodynamic conditions and dynamical nature of protons,beyond the capability of the traditional lattice dynamics and empirical potential molecular dynamics *** utilizing the deep potential molecular dynamics approach,we investigate the thermal conductivity of ice-Ⅶ and superionic ice-Ⅶ’’ along the isobar of P = 30 GPa.A non-monotonic trend of thermal conductivity with elevated temperature is *** heat flux decomposition and trajectory-based spectra analysis,we show that the thermally activated proton diffusion in ice-Ⅶ and superionic ice-Ⅶ′′contribute significantly to heat convection,while the broadening in vibrational energy peaks and significant softening of transverse acoustic branches lead to a reduction in heat *** competition between proton diffusion and phonon scattering results in anomalous thermal transport across the superionic transition in *** work unravels the important role of proton diffusion in the thermal transport of high-pressure *** approach provides new insights into modeling the thermal transport and atomistic dynamics in superionic materials.

关键词： ionic Transition utilizing

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Convergence analysis of a Legendre spectral collocation method for nonlinear Fredholm integral equations in multidimensions

Convergence analysis of a Legendre spectral collocation meth...

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作者： Zaky, Mahmoud A. Hendy, Ahmed S. Department of Applied Mathematics National Research Centre Cairo Egypt Department of Mathematics Faculty of Science Benha University Benha Egypt Department of Computational Mathematics and Computer Science Institute of Natural Sciences and Mathematics Ural Federal University Yekaterinburg Russia

It is a very challenging task to solve a nonlinear integral equation in multidimensions. The main purpose of this paper is to develop and analyze a spectral collocation method for a class of nonlinear Fredholm integral equations of the second kind in multidimensions. The proposed spectral collocation method is based on a multivariate Legendre approximation in the frequency space. It is shown by both theory and numerics that the proposed spectral collocation scheme not only significantly reduces the number of degrees of freedom but also produces very accurate approximations. © 2020 John Wiley & Sons, Ltd.

关键词： Fredholm integral equations

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Uniform local well-posedness and inviscid limit for the Benjamin-Ono-Burgers equation

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Science China mathematics 2022年第8期65卷 1553-1576页

作者： Mingjuan Chen Boling Guo Lijia Han Department of Mathematics Jinan UniversityGuangzhou510632China Institute of Applied Physics and Computational Mathematics Beijing100088China Department of Mathematics and Physics North China Electric Power UniversityBeijing102206China

In this paper,we study the Cauchy problem for the Benjamin-Ono-Burgers equation ∂_(t)u−ϵ∂^(2)/_(x)u+H∂^(2)_(x)u+uu_(x)=0,where H denotes the Hilbert transform *** obtain that it is uniformly locally well-posed for small data in the refined Sobolev space H~σ(R)(σ■0),which is a subspace of L2(ℝ).It is worth noting that the low-frequency part of H~σ(R)is scaling critical,and thus the small data is *** high-frequency part of H~σ(R)is equal to the Sobolev space Hσ(ℝ)(σ■0)and reduces to L2(ℝ).Furthermore,we also obtain its inviscid limit behavior in H~σ(R)(σ■0).

关键词： Benjamin-Ono-Burgers equation Cauchy problem inviscid limit behavior

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Spectroscopy and molecule opacity investigation on excited states of SiS

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Chinese Physics B 2024年第5期33卷 381-387页

作者：李瑞吕浩男桑纪群刘晓华梁桂颖吴勇 College of Teacher Education Qiqihar UniversityQiqihar 161006China National Key Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China Department of Physics College of ScienceQiqihar UniversityQiqihar 161006China School of Data Science and Artificial Intelligence Jilin Engineering Normal UniversityChangchun 130052China HEDPS Center for Applied Physics and TechnologyPeking UniversityBeijing 100084China

The SiS molecule,which plays a significant role in space,has attracted a great deal of attention for many *** to complex interactions among its low-lying electronic states,precise information regarding the molecular structure of SiS is *** obtain accurate information about the structure of its excited states,the high-precision multireference configuration interaction(MRCI)method has been *** method is used to calculate the potential energy curves(PECs)of the 18Λ–S states corresponding to the lowest dissociation limit of *** core–valence correlation effect,Davidson’s correction and the scalar relativistic effect are also included to guarantee the precision of the MRCI *** on the calculated PECs,the spectroscopic constants of quasi-bound and bound electronic states are calculated and they are in accordance with previous experimental *** transition dipole moments(TDMs)and dipole moments(DMs)are determined by the MRCI *** addition,the abrupt variations of the DMs for the 1^(5)Σ^(+)and 2^(5)Σ^(+)states at the avoided crossing point are attributed to the variation of the electronic *** opacity of SiS at a pressure of 100 atms is presented across a series of *** increasing temperature,the expanding population of excited states blurs the band boundaries.

关键词： SiS opacity excited state spectroscopic constant configuration interaction

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Evaluation of Various Machine Learning Algorithms for Seed Prediction Based on the Soil Nutrient Quantification 2nd

Evaluation of Various Machine Learning Algorithms for Seed P...

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2nd International Conference on Intelligent Computing Systems and Applications, ICICSA 2023

作者： Ramprakash, Balakrishnan Muthuramalingam, Sankayya Department of Applied Mathematics and Computational Science Thiagarajar College of Engineering Madurai India Department of Information Technology Thiagarajar College of Engineering Madurai India

ISBN: (纸本)9789819754113

The current condition of the soil is an important consideration in crop yield projections. An analysis of the soil’s nutrient content can help farmers and soil analysts obtain a higher yield of seedlings suited to the cultivation process by facilitating the necessary preparations. This study presents a number of machine learning techniques that have been implemented in order to predict seedlings based on soil nutrient measurements. The department of Agriculture department in South Tamil Nadu provided the data that was used in this research experimental design. This data includes soil nutrient level samples from a variety of districts located throughout the South Tamil Nadu region for a selection of districts. The evaluation of crop yields is becoming an increasingly important area of research, including machine learning. The challenge of accurately predicting yields is an extremely significant one in the agricultural industry. Any farmer worth his salt is going to want to know how much yield he may anticipate receiving from his next harvest. In the past, predictions of yield were made by factoring in the years of experience that farmers had gained working with a certain crop and field. On the basis of the data that is now available, the prediction of the yield is a significant problem that has not yet been resolved. The implementation of methods that are driven by machine learning is the approach that is going to be most successful in achieving this objective. Five supervised machine learning methods were used to analyze the study’s data: DT, NB, SVM, RF, and LR are codes for the following: Follow these ML classification techniques to plainly categorize the results. Regression is a form of supervised learning algorithm used to predict a continuous output variable given one or more predictors or features, also known as input variables. Experiments have been carried out in order to discover the method that is the most accurate in terms of seed prediction for the purpo

关键词： Adversarial machine learning

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Singular limits for the Navier-Stokes-Poisson equations of the viscous plasma with the strong density boundary layer

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Science China mathematics 2023年第7期66卷 1495-1528页

作者： Qiangchang Ju Tao Luo Xin Xu Institute of Applied Physics and Computational Mathematics Beijing 100088China Department of Mathematics City University of Hong KongHong KongChina School of Mathematical Sciences and College of Oceanic and Atmospheric Sciences Ocean University of ChinaQingdao 266100China

The quasi-neutral limit of the Navier-Stokes-Poisson system modeling a viscous plasma with vanishing viscosity coefficients in the half-space■is rigorously proved under a Navier-slip boundary condition for velocity and the Dirichlet boundary condition for electric *** is achieved by establishing the nonlinear stability of the approximation solutions involving the strong boundary layer in density and electric potential,which comes from the breakdown of the quasi-neutrality near the boundary,and dealing with the difficulty of the interaction of this strong boundary layer with the weak boundary layer of the velocity field.

关键词： Navier-Stokes-Poisson equations interaction of strong and weak boundary layers singular limit

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