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Kinetic model of vibration screening for granular materials based on biological neural network

Particuology 2024年第5期88卷 98-106页

作者： Zhan Zhao Yan Zhang Fang Qin Mingzhi Jin School of Agricultural Engineering Jiangsu UniversityZhenjiang212013China Shandong Academy of Agricultural Machinery Sciences Ji'nan250100China

The kinetic model is the theoretical basis for optimizing the structure and operation performance of vibration screening *** this paper,a biological neurodynamic equation and neural connections were established according to the motion and interaction properties of the material under vibration *** material feeding to the screen and the material passing through apertures were considered as excitatory and inhibitory inputs,respectively,and the generated stable neural activity landscape was used to describe the material distribution on the 2D screen *** dynamic process of material vibration screening was simulated using discrete element method(DEM).By comparing the similarity between the material distribution established using biological neural network(BNN)and that obtained using DEM simulation,the optimum coefficients of BNN model under a certain screening parameter were determined,that is,one relationship between the BNN model coefficients and the screening operation parameters was *** screening parameters were randomly selected,and the corresponding relationships were established as a ***,with straw/grain ratio,aperture diameter,inclination angle,vibration strength in normal and tangential directions as inputs,five independent adaptive neuro-fuzzy inference systems(ANFIS)were established to predict the optimum BNN model coefficients,*** training results indicated that ANFIS models had good stability and *** flexibility and adaptability of the proposed BNN method was demonstrated by modeling material distribution under complex feeding conditions such as multiple regions and non-uniform rate.

关键词： Kinetic model Material distribution Vibration screening biological neural network DEM simulation Adaptive neuro-fuzzy inference systems

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Leveraging Quantum Computing for the Ising Model to Simulate Two Real Systems: Magnetic Materials and biological neural networks (BNNs)

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Journal of Quantum Information Science 2023年第3期13卷 138-155页

作者： David L. Cao Khoi Dinh Thomas Jefferson High School for Science and Technology Alexandria VA USA

Quantum computing is a field with increasing relevance as quantum hardware improves and more applications of quantum computing are discovered. In this paper, we demonstrate the feasibility of modeling Ising Model Hamiltonians on the IBM quantum computer. We developed quantum circuits to simulate these systems more efficiently for both closed and open boundary Ising models, with and without perturbations. We tested these various geometries of systems in both 1-D and 2-D space to mimic two real systems: magnetic materials and biological neural networks (BNNs). Our quantum model is more efficient than classical computers, which can struggle to simulate large, complex systems of particles.

关键词： Ising Model Magnetic Material biological neural network Quantum Computting International Business Machines (IBM)

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Effective Diagnosis of Lung Cancer via Various Data-Mining Techniques

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Intelligent Automation & Soft Computing 2023年第4期36卷 415-428页

作者： Subramanian Kanageswari D.Gladis Irshad Hussain Sultan S.Alshamrani Abdullah Alshehri Bharathiar University Coimbatore641046India Bharathi Women’s College Chennai600108India Faculty of Electrical and Computer Engineering University of Engineering and TechnologyPeshawar25000PeshawarPakistan Department of Information Technology College of Computer and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Information Technology Al Baha UniversityP.O.Box 1988Al Baha65431Saudi Arabia

One of the leading cancers for both genders worldwide is lung *** occurrence of lung cancer has fully augmented since the early 19th *** this manuscript,we have discussed various data mining techniques that have been employed for cancer *** to air pollution has been related to various adverse health *** work is subject to analysis of various air pollutants and associated health hazards and intends to evaluate the impact of air pollution caused by lung *** have introduced data mining in lung cancer to air pollution,and our approach includes preprocessing,data mining,testing and evaluation,and knowledge ***,we will eradicate the noise and irrelevant data,and following that,we will join the multiple informed sources into a common *** that source,we will designate the information relevant to our investigation to be regained from that *** that,we will convert the designated data into a suitable mining *** patterns are abstracted by utilizing a relational suggestion rule mining *** patterns have revealed information,and this information is categorized with the help of an Auto Associative neural network classiﬁcation method(AANN).The proposed method is compared with the existing method in various *** conclusion,the projected Auto associative neural network and relational suggestion rule mining methods accomplish a high accuracy status.

关键词： Relational association rule mining auto associative neural network preprocessing data mining biological neural network

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大脑皮层内神经元集团的能量演变

大脑皮层内神经元集团的能量演变

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第十一届全国非线性振动学术会议暨第八届全国非线性动力学和运动稳定性学术会议

作者：王如彬张志康沈恩华上海华东理工大学信息科学与工程学院脑信息处理与认知神经动力学研究中心

本文在能量编码原理的基础上,利用哈密尔顿函数得到了大脑皮层内大规模神经元集群在阈下和阈上互相耦合时神经元电位变化的能量函数。根据神经电生理的实验数据得到了高斯白噪声条件下神经元电位活动的膜电位运动方程。研究结果表明本... 详细信息

本文在能量编码原理的基础上,利用哈密尔顿函数得到了大脑皮层内大规模神经元集群在阈下和阈上互相耦合时神经元电位变化的能量函数。根据神经电生理的实验数据得到了高斯白噪声条件下神经元电位活动的膜电位运动方程。研究结果表明本文得到的膜电位的均值恰是我们先前已发表的膜电位运动方程的精确解。并且我们还得到了神经元集群编码的哈密尔顿函数随时间的演变过程,即神经元集群随时间的能量演化过程的定量表达式。

关键词： neural population energy coding Hamiltonian function biological neural network

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