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A Study on New Control Mechanisms of Memory
Haibin LIU,Yukinori KAKAZU 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
A physical phenomenon is observed through analysis of the Hodgkin-Huxley's model that is, according to Maxwell field equations a fired neuron can yield magnetic fields. The magnetic signals are an output of the neuron as some type of information, which may be supposed to be the conscious control information. Therefore, study on neural networks should take the field effect into consideration. Accordingly, a study on the behavior of a unit neuron in the field is made and a new neuron model is proposed. A mathematical Memory-Learning Relation has been derived from these new neuron equations, some concepts of memory and learning are introduced. Two learning theorems are put forward, and the control mechanisms of memory are also discussed. Finally, a theory, i.e. Neural Electromag metic(NEM) field theory is advanced.
Haibin Li,Bo Liu,Li Li,Qian Zhang,Chengwei Huang 대한토목학회 2024 KSCE Journal of Civil Engineering Vol.28 No.6
In the methods for mitigating the effect of foundation pit excavation on underlying tunnel, the conventional analytical calculation method adopted the elastic foundation beam to derive the tunnel deformation and internal forces. However, this traditional approach assumes that the released stress is loaded on the excavation face and subsequently affects the tunnel stress, which can be obtained by Mindlin’s solution. The limitations of this method are analyzed, and the soil deformation caused by excavation is introduced as an external load in the model. A differential equation of the elastic foundation beam is established and used to derive the analytic solution of the deformation and internal force of the tunnel by analysis of the empirical formula of soil deformation under foundation pit. Additionally, the weighted residual solution is introduced due to the difficulty in calculation of analytic solution. Considering that the project in this study is a three-dimensional problem?the torque is derived for a complete elastic foundation beam solution.
Liu Dongmei,Ouyang Haibin,Li Steven,장춘량,Zhan Zhi-Hui 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.4
Because of the good performance of convolutional neural network (CNN), it has been extensively used in many fields, such as image, speech, text, etc. However, it is easily affected by hyperparameters. How to effectively configure hyperparameters at a reasonable time to improve the performance of CNNs has always been a complex problem. To solve this problem, this paper proposes a method to automatically optimize CNN hyperparameters based on the local autonomous competitive harmony search (LACHS) algorithm. To avoid the influence of complicated parameter adjustment of LACHS algorithm on its performance, a parameter dynamic adjustment strategy is adopted, which makes the pitch adjustment probability PAR and step factor BW dynamically adjust according to the actual situation. To strengthen the fine search of neighborhood space and reduce the possibility of falling into local optima for a long time, an autonomous decision-making search strategy based on the optimal state is designed. To help the algorithm jump out of the local fitting situation, this paper proposes a local competition mechanism to make the new sound competes with the worst harmonic progression of local selection. In addition, an evaluation function is proposed, which integrates the training times and recognition accuracy. To achieve the purpose of saving the calculation cost without affecting the search result, it makes the training time for each model depending on the learning rate and batch size. In order to prove the feasibility of LACHS algorithm in configuring CNN superparameters, the classification of the Fashion-MNIST dataset and CIFAR10 dataset is tested. The comparison is made between CNN based on empirical configuration and CNN based on classical algorithms to optimize hyperparameters automatically. The results show that the performance of CNN based on the LACHS algorithm has been improved effectively, so this algorithm has certain advantages in hyperparametric optimization. In addition, this paper applies the LACHS algorithm to expression recognition. Experiments show that the performance of CNN optimized based on the LACHS algorithm is better than that of the same type of artificially designed CNN. Therefore, the method proposed in this paper is feasible in practical application.
Kinetic modeling for chromatographic separation of cytosine monophosphate and uracil monophosphate
Haibin Qu,Yong Chen,Weixing Dai,Xuesong Liu,Yiyu Cheng 한국화학공학회 2006 Korean Journal of Chemical Engineering Vol.23 No.5
pharmaceutical industries. In this study, chromatographic separation of the two nucleotides CMP and UMP was sim-ulated by the equilibrium-dispersive (ED) model, and the adsorption isotherms in the ED model were determined bythe inverse method. Prediction performance of the model was validated under three diferent kinds of conditions andthe importance of selecting isotherms was discussed in detail. Excellent agreement was achieved with the experi-mental band profiles and the prediction of the ED model. The ED model with bi-Langmuir isotherm was especiallysuitable for simulating chromatographic separation of CMP and UMP. The error of prediction by the ED model with