Physical Sciences and Mathematics Commons^™

Multi-Objective Optimization Design Of Aerodynamic Layout For Twin Swept-Wing Aircraft, Yuchang Lei, Dengcheng Zhang, Yanhua Zhang, Guangxu Su, Luo Hao, Zhan Ren

Journal of System Simulation

Abstract: Multi-objective optimization of aerodynamic layout is a key technology in the design of vehicles. The overall configuration of the shape parameters is optimized with a double swept-shaped wave shape as the basic configuration. We use NSGA-Ⅱ multi-objective genetic algorithm, take the aircraft double sweep angle as the design variable, consider the maximum takeoff weight, range, volume ratio and other performance indicators, use Elman neural network to establish the relationship between shape parameters and performance parameters, and establish constraints based on mission planning requirements. The Pareto optimal solution set is obtained by using optimized design and the individuals with …

Robot Arm Control Method Based On Deep Reinforcement Learning, Heyu Li, Zhilong Zhao, Gu Lei, Liqin Guo, Zeng Bi, Tingyu Lin

Journal of System Simulation

Abstract: Deep reinforcement learning continues to explore in the environment and adjusts the neural network parameters by the reward function. The actual production line can not be used as the trial and error environment for the algorithm, so there is not enough data. For that, this paper constructs a virtual robot arm simulation environment, including the robot arm and the object. The Deep Deterministic Policy Gradient (DDPG),in which the state variables and reward function are set,is trained by deep reinforcement learning algorithm in the simulation environment to realize the target of controlling the robot arm to move the gripper below …

Identification And Prediction Of Room Temperature Delay Neural Network Model For Vav Air Conditioning, Xiuming Li, Jili Zhang, Tianyi Zhao, Tingting Chen

Journal of System Simulation

Abstract: Aiming at the problem of mathematical description for dynamic response characteristic of indoor temperature time-delay system, the fundamental principle of neural network model identification is introduced in regulation process of variable air volume (VAV) air conditioning system. Considering the model structure of Elman neural network, this paper presents an optimal selection algorithm for layer delay coefficient in order to determine delay time between indoor temperature and regulation parameters; and a multiple-step prediction model of indoor temperature time-delay system based on Elman neural network is built. The effectiveness of the proposed method is validated through the simulation experiment.

Semi-Supervised Regression With Generative Adversarial Networks Using Minimal Labeled Data, Greg Olmschenk

Dissertations, Theses, and Capstone Projects

This work studies the generalization of semi-supervised generative adversarial networks (GANs) to regression tasks. A novel feature layer contrasting optimization function, in conjunction with a feature matching optimization, allows the adversarial network to learn from unannotated data and thereby reduce the number of labels required to train a predictive network. An analysis of simulated training conditions is performed to explore the capabilities and limitations of the method. In concert with the semi-supervised regression GANs, an improved label topology and upsampling technique for multi-target regression tasks are shown to reduce data requirements. Improvements are demonstrated on a wide variety of vision …

Topic Classification Using Hybrid Of Unsupervised And Supervised Learning, Jayant Shelke

Master's Projects

There has been research around the idea of representing words in text as vectors and many models proposed that vary in performance as well as applications. Text processing is used for content recommendation, sentiment analysis, plagiarism detection, content creation, language translation, etc. to name a few. Specifically, we want to look at the problem of topic detection in text content of articles/blogs/summaries. With the humungous amount of text content published each and every minute on the internet, it is imperative that we have very good algorithms and approaches to analyze all the content and be able to classify most of …

New Clock-Driven Algorithm Based On Separation Of Synaptic Conductance Computation, Zhijie Wang, Peng Xia, Han Fang, Xiaochun Gu

Journal of System Simulation

Abstract: In order to reduce the computing time when simulating the biologic neural network, an efficient clock-driven algorithm based on the separation of synaptic conductance computation is presented. It is found that the calculation of the synaptic state variables can be separated into two independent parts: one called conductance coefficient related with the pre-synaptic neuron, and the other called synaptic current. By introducing the data structure of the virtual synapse cluster to storing sequences of synaptic conductance coefficient, the former part can be calculated independently according to the spiking states of pre-synaptic neuron at each time step. When calculating the …

Artificial Fish Swarm And Feedback Linearization Of Flue Gas Denitration Control Based On Neural Network, Yuguang Niu, Pan Yan, Wenyuan Huang

Journal of System Simulation

Abstract: According to the present situation of SCR flue gas dentration control system in thermal power plant, an optimum proposal that control valve and concentration transmitter are added in the inlet of the SCR reactor is presented, and the corresponding control strategy is given. At the entrance of the SCR reactor, the receding horizon algorithm combined with the single neuron adaptive algorithm and the artificial fish swarm algorithm (RSNAAFS) is used to control branch valves to pretreat NO_X in the exhaust flue gas. At the outlet of the SCR reactor, the neural network based on feedback linearization algorithm (NNFL) …

Research On Interaction Model Of Hand Tracking Based On Cognitive Theory, Shaobai Zhang, Zhang Teng

Journal of System Simulation

Abstract: This paper aims to solve the problems in a vector integration to endpoint (VITE) model of human reaching and grasping under perturbations of object size, distance and orientation. We discuss how to reduce the numbers of disturbances of three main kinds of components: hand/wrist transport, grip aperture and hand orientation. Based on the achievements of cognitive psychology, and a tracking and cognitive model for operational 3D gestures, this paper proposes a new divide-and-conquer model that is used for indicating current grasping status and to trigger three main kinds of methods of when to start or stop working. The model …

Error Estimation For Material Simulation Data Based On Hybrid Learning Algorithm, Wang Juan, Xiaoyu Yang, Zongguo Wang, Ren Jie, Xushan Zhao

Journal of System Simulation

Abstract: In order to obtain high quality material simulation data from Density Functional Theory material calculation software package, a modeling method based on BP neural network was proposed to build model estimating the error of material simulation data. A novel hybrid algorithm combining simple particle swarm optimization algorithm that excludes speed item with BP algorithm, also referred to tsPSO-BP, was proposed to optimize the connection weights of the BP neural network. The hybrid learning algorithm not only makes use of strong global searching ability of the PSO, but also strong local searching ability of the BP algorithm. The BP …

Prediction Of Aircraft Cabin Energy Consumption Based On Improved Cooperative Pso Neural Network, Xiuyan Wang, Yanmin Liu, Gewen Zhang, Zongshuai Li, Jiaquan Lin

Journal of System Simulation

Abstract: To correctly evaluate the energy needs of the aircraft cabin and to predict the energy consumption of the aircraft cabin with higher accuracy, an energy consumption prediction method based on improved particle swarm optimization (PSO) neural network algorithm parameters is proposed. The method combines the cooperative particle swarm optimization algorithm with chaotic particle swarm optimization algorithm. On the basis of cooperative particle swarm optimization algorithm chaos theory is introduced. Continuous search ability by using chaos optimization method to overcome the collaborative optimization algorithm is easy to fall into the local extremum problem. The parameters of the neural network can …

Optimization Via Simulation Based On Neural Network, Shihui Wu, Xiaodong Liu, Shao Yue, Zhang Fa, Minxiang Yang

Journal of System Simulation

Abstract: To improve the efficiency of optimization via simulation (OvS), an OvS method based on neural network is proposed. Taking advantage of the approximation ability of neural network to nonlinear input-output relationship, neural network's outputs are used as substitutes for simulation results to reduce the required simulation runs. Samples are generated by simulation according to the three proposed samples selection methods. Owning to its advantages on learning speed, network stability and parameters selection, generalized regression neural network (GRNN) is adopted to train the samples. The trained GRNN forms a regression surface that represents the relationship between simulation inputs and outputs, …

Multi-Response Parameters Optimization Based On Pca And Neural Network, Jianli Yu, Hongqi Huang, Manxiang Miao

Journal of System Simulation

Abstract: A multi-response parameters optimization method based on principal component analysis (PCA) and neural network is proposed. It is used to optimize temperature and time parameters in complex thermal polymerization process. By using the method of weighted PCA, two response indexes, capacity value and loss tangent value, are converted into a single quality performance index. The main effect value is used to identify the search range. The radical basis function (RBF) neural network model is established to search and identify the optimal process parameters. Results show that response indexes are improved and the optimization effect is obvious. Therefore, this study …

Applied Machine Learning For Classification Of Musculoskeletal Inference Using Neural Networks And Component Analysis, Shaswat Sharma

Electronic Theses and Dissertations

Artificial Intelligence (AI) is acquiring more recognition than ever by researchers and machine learning practitioners. AI has found significance in many applications like biomedical research for cancer diagnosis using image analysis, pharmaceutical research, and, diagnosis and prognosis of diseases based on knowledge about patients' previous conditions. Due to the increased computational power of modern computers implementing AI, there has been an increase in the feasibility of performing more complex research.

Within the field of orthopedic biomechanics, this research considers complex time-series dataset of the "sit-to-stand" motion of 48 Total Hip Arthroplasty (THA) patients that was collected by the Human Dynamics …