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Дисертації з теми "Seasonal Artificial Neural Network"

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Автор: Grafiati
Опубліковано: 19 червня 2021
Оновлено: 1 лютого 2022

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1

Widing, Härje. "Business analytics tools for data collection and analysis of COVID-19." Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176514.

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Анотація:
The pandemic that struck the entire world 2020 caused by the SARS-CoV-2 (COVID-19) virus, will have an enormous interest for statistical and economical analytics for a long time. While the pandemic of 2020 is not the first that struck the entire world, it is the first pandemic in history where the data were gathered to this extent. Most countries have collected and shared its numbers of cases, tests and deaths related to the COVID-19 virus using different storage methods and different data types. Gaining quality data from the COVID-19 pandemic is a problem most countries had during the pandemic, since it is constantly changing not only for the current situation but also because past values have been altered when additional information has surfaced. The importance of having the latest data available for government officials to make an informed decision, leads to the usage of Business Intelligence tools and techniques for data gathering and aggregation being one way of solving the problem. One of the mostly used software to perform Business Intelligence is the Microsoft develop Power BI, designed to be a powerful visualizing and analysing tool, that could gather all data related to the COVID-19 pandemic into one application. The pandemic caused not only millions of deaths, but it also caused one of the largest drops on the stock market since the Great Recession of 2007. To determine if the deaths or other reasons directly caused the drop, the study modelled the volatility from index funds using Generalized Autoregressive Conditional Heteroscedasticity. One question often asked when talking of the COVID-19 virus, is how deadly the virus is. Analysing the effect the pandemic had on the mortality rate is one way of determining how the pandemic not only affected the mortality rate but also how deadly the virus is. The analysis of the mortality rate was preformed using Seasonal Artificial Neural Network. Forecasting deaths from the pandemic using the Seasonal Artificial Neural Network on the COVID-19 daily deaths data.
2

BRUCE, WILLIAM, and OTTER EDVIN VON. "Artificial Neural Network Autonomous Vehicle : Artificial Neural Network controlled vehicle." Thesis, KTH, Maskinkonstruktion (Inst.), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191192.

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This thesis aims to explain how a Artificial Neural Network algorithm could be used as means of control for a Autonomous Vehicle. It describes the theory behind the neural network and Autonomous Vehicles, and how a prototype with a camera as its only input can be designed to test and evaluate the algorithms capabilites, and also drive using it. The thesis will show that the Artificial Neural Network can, with a image resolution of 100 × 100 and a training set with 900 images, makes decisions with a 0.78 confidence level.
Denna rapport har som mal att beskriva hur en Artificiellt Neuronnatverk al- goritm kan anvandas for att kontrollera en bil. Det beskriver teorin bakom neu- ronnatverk och autonoma farkoster samt hur en prototyp, som endast anvander en kamera som indata, kan designas for att testa och utvardera algoritmens formagor. Rapporten kommer visa att ett neuronnatverk kan, med bildupplos- ningen 100 × 100 och traningsdata innehallande 900 bilder, ta beslut med en 0.78 sakerhet.
3

Leija, Carlos Ivan. "An artificial neural network with reconfigurable interconnection network." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2008. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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4

Alkharobi, Talal M. "Secret sharing using artificial neural network." Diss., Texas A&M University, 2004. http://hdl.handle.net/1969.1/1223.

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Secret sharing is a fundamental notion for secure cryptographic design. In a secret sharing scheme, a set of participants shares a secret among them such that only pre-specified subsets of these shares can get together to recover the secret. This dissertation introduces a neural network approach to solve the problem of secret sharing for any given access structure. Other approaches have been used to solve this problem. However, the yet known approaches result in exponential increase in the amount of data that every participant need to keep. This amount is measured by the secret sharing scheme information rate. This work is intended to solve the problem with better information rate.
5

Zhao, Lichen. "Random pulse artificial neural network architecture." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0006/MQ36758.pdf.

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6

Ng, Justin. "Artificial Neural Network-Based Robotic Control." DigitalCommons@CalPoly, 2018. https://digitalcommons.calpoly.edu/theses/1846.

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Artificial neural networks (ANNs) are highly-capable alternatives to traditional problem solving schemes due to their ability to solve non-linear systems with a nonalgorithmic approach. The applications of ANNs range from process control to pattern recognition and, with increasing importance, robotics. This paper demonstrates continuous control of a robot using the deep deterministic policy gradients (DDPG) algorithm, an actor-critic reinforcement learning strategy, originally conceived by Google DeepMind. After training, the robot performs controlled locomotion within an enclosed area. The paper also details the robot design process and explores the challenges of implementation in a real-time system.
7

Khazanova, Yekaterina. "Experiments with Neural Network Libraries." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1527607591612278.

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8

Brunger, Clifford A. "Artificial neural network modeling of damaged aircraft." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA283227.

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9

Tang, Chuan Zhang. "Artificial neural network models for digital implementation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq30298.pdf.

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10

Tupas, Ronald-Ray Tiñana. "Artificial neural network modelling of filtration performance." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0011/MQ59890.pdf.

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11

Luan, Wenpeng. "Voltage ranking using artificial neural network method." Thesis, University of Strathclyde, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366960.

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12

Bataineh, Mohammad Hindi. "Artificial neural network for studying human performance." Thesis, University of Iowa, 2012. https://ir.uiowa.edu/etd/3259.

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The vast majority of products and processes in industry and academia require human interaction. Thus, digital human models (DHMs) are becoming critical for improved designs, injury prevention, and a better understanding of human behavior. Although many capabilities in the DHM field continue to mature, there are still many opportunities for improvement, especially with respect to posture- and motion-prediction. Thus, this thesis investigates the use of artificial neural network (ANN) for improving predictive capabilities and for better understanding how and why human behave the way they do. With respect to motion prediction, one of the most challenging opportunities for improvement concerns computation speed. Especially, when considering dynamic motion prediction, the underlying optimization problems can be large and computationally complex. Even though the current optimization-based tools for predicting human posture are relatively fast and accurate and thus do not require as much improvement, posture prediction in general is a more tractable problem than motion prediction and can provide a test bead that can shed light on potential issues with motion prediction. Thus, we investigate the use of ANN with posture prediction in order to discover potential issues. In addition, directly using ANN with posture prediction provides a preliminary step towards using ANN to predict the most appropriate combination of performance measures (PMs) - what drives human behavior. The PMs, which are the cost functions that are minimized in the posture prediction problem, are typically selected manually depending on the task. This is perhaps the most significant impediment when using posture prediction. How does the user know which PMs should be used? Neural networks provide tools for solving this problem. This thesis hypothesizes that the ANN can be trained to predict human motion quickly and accurately, to predict human posture (while considering external forces), and to determine the most appropriate combination of PM(s) for posture prediction. Such capabilities will in turn provide a new tool for studying human behavior. Based on initial experimentation, the general regression neural network (GRNN) was found to be the most effective type of ANN for DHM applications. A semi-automated methodology was developed to ease network construction, training and testing processes, and network parameters. This in turn facilitates use with DHM applications. With regards to motion prediction, use of ANN was successful. The results showed that the calculation time was reduced from 1 to 40 minutes, to a fraction of a second without reducing accuracy. With regards to posture prediction, ANN was again found to be effective. However, potential issues with certain motion-prediction tasks were discovered and shed light on necessary future development with ANNs. Finally, a decision engine was developed using GRNN for automatically selecting four human PMs, and was shown to be very effective. In order to train this new approach, a novel optimization formulation was used to extract PM weights from pre-existing motion-capture data. Eventually, this work will lead to automatically and realistically driving predictive DHMs in a general virtual environment.
13

Choi, Hyunjong. "Medical Image Registration Using Artificial Neural Network." DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1523.

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Image registration is the transformation of different sets of images into one coordinate system in order to align and overlay multiple images. Image registration is used in many fields such as medical imaging, remote sensing, and computer vision. It is very important in medical research, where multiple images are acquired from different sensors at various points in time. This allows doctors to monitor the effects of treatments on patients in a certain region of interest over time. In this thesis, artificial neural networks with curvelet keypoints are used to estimate the parameters of registration. Simulations show that the curvelet keypoints provide more accurate results than using the Discrete Cosine Transform (DCT) coefficients and Scale Invariant Feature Transform (SIFT) keypoints on rotation and scale parameter estimation.
14

Chambers, Mark Andrew. "Queuing network construction using artificial neural networks /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488193665234291.

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15

Tsui, Kwok Ching. "Neural network design using evolutionary computing." Thesis, King's College London (University of London), 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299918.

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16

Baker, Thomas Edward. "Implementation limits for artificial neural networks." Full text open access at:, 1990. http://content.ohsu.edu/u?/etd,268.

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17

Leong, Cheok Fan. "Approximation theory of multilayer feedforward artificial neural network." Thesis, University of Macau, 2002. http://umaclib3.umac.mo/record=b1446728.

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18

Beckenkamp, Fábio Ghignatti. "A component architecture for artificial neural network systems." [S.l. : s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=964923580.

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19

Theramongkol, Phunsak. "Intelligent ozone-level forecasting using artificial neural network." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0021/MQ54752.pdf.

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20

Zahra, Fathima. "Artificial neural network approach to transmission line relaying." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0001/MQ42465.pdf.

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21

Thirkell, Lawrence Alexander. "An artificial neural network approach to authorship determination." Thesis, Heriot-Watt University, 1993. http://hdl.handle.net/10399/1418.

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22

Johnson, D. E. "Analogue VLSI implementation of an artificial neural network." Thesis, University of Liverpool, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367276.

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23

Chan, Kwok Hung Billy Carleton University Dissertation Engineering Mechanical and Aerospace. "Predicting weld features using artificial neural network technology." Ottawa, 1996.

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24

Mryyan, Mahmoud. "Environmental site characterization via artificial neural network approach." Diss., Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/1120.

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25

Wu, Chung-Yu. "Predicting water table fluctuations using artificial neural network." College Park, Md.: University of Maryland, 2008. http://hdl.handle.net/1903/8826.

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Анотація:
Thesis (Ph. D.) -- University of Maryland, College Park, 2008.
Thesis research directed by: Fischell Dept. of Bioengineering . Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
26

Kannemeyer, Johan Etienne. "Artificial neural network decoding of multi-h CPM." Master's thesis, University of Cape Town, 1997. http://hdl.handle.net/11427/19638.

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Анотація:
The purpose of this report is to set out the results of an investigation into the artificial neural network (ANN) decoding of multi-h continuous phase modulation (CPM) schemes. Multi-h CPM schemes offer forward error correction (FEC) capabilities for continuous transmission, digital communication systems. Multi-h CPM is reported to be a bandwidth efficient alternative to other FEC techniques such as convolutional coding, while neural networks allow for high speed decoding. A neural network decoder was found in [12], where it had been used for the decoding of a convolutional code. This neural network structure by Xiao-an Wang and Stephen 'B. Wicker implements the Viterbi Algorithm (VA). All the necessary decoding information is contained in the interconnections of the ANN, and can be found by inspection of the state trellis diagram of the convolutional code. The decoder therefore requires no training. Since all the computation is done by analogue neurons and shift registers, the neural network reduces to a hybrid digital-analogue implementation of the VA. The use of analogue neurons allows the structure to be used for high data rate communications. Furthermore, the decoder is reported to be suitable for VLSI implementation.
27

Keisala, Simon. "Designing an Artificial Neural Network for state evaluation in Arimaa : Using a Convolutional Neural Network." Thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-143188.

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Agents being able to play board games such as Tic Tac Toe, Chess, Go and Arimaa has been, and still is, a major difficulty in Artificial Intelligence. For the mentioned board games, there is a certain amount of legal moves a player can do in a specific board state. Tic Tac Toe have in average around 4-5 legal moves, with a total amount of 255168 possible games. Both Chess, Go and Arimaa have an increased amount of possible legal moves to do, and an almost infinite amount of possible games, making it impossible to have complete knowledge of the outcome. This thesis work have created various Neural Networks, with the purpose of evaluating the likelihood of winning a game given a certain board state. An improved evaluation function would compensate for the inability of doing a deeper tree search in Arimaa, and the anticipation is to compete on equal skills against another well-performing agent (meijin) having one less search depth. The results shows great potential. From a mere one hundred games against meijin, the network manages to separate good from bad positions, and after another one hundred games able to beat meijin with equal search depth. It seems promising that by improving the training and by testing different sizes for the neural network that a neural network could win even with one less search depth. The huge branching factor of Arimaa makes such an improvement of the evaluation beneficial, even if the evaluation would be 10 000 times more slow.
28

Åström, Fredrik. "Neural Network on Compute Shader : Running and Training a Neural Network using GPGPU." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2036.

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In this thesis I look into how one can train and run an artificial neural network using Compute Shader and what kind of performance can be expected. An artificial neural network is a computational model that is inspired by biological neural networks, e.g. a brain. Finding what kind of performance can be expected was done by creating an implementation that uses Compute Shader and then compare it to the FANN library, i.e. a fast artificial neural network library written in C. The conclusion is that you can improve performance by training an artificial neural network on the compute shader as long as you are using non-trivial datasets and neural network configurations.
29

Xu, Le Yan. "Artificial neural network short-term electrical load forecasting techniques." Thesis, University of Macau, 1999. http://umaclib3.umac.mo/record=b1445624.

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30

Tracy, Justin. "Prediction of wind speeds with an artificial neural network." Click here to view, 2010. http://digitalcommons.calpoly.edu/eesp/24/.

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Анотація:
Thesis (B.S.)--California Polytechnic State University, 2010.
Project advisor: Xiao-Hua Yu. Title from PDF title page; viewed on Apr. 20, 2010. Includes bibliographical references. Also available on microfiche.
31

Moshiri, Saeed. "Forecasting inflation using econometric and artificial neural network models." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ32008.pdf.

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32

Baxter, Christopher Wayne. "Full-scale artificial neural network modelling of enhanced coagulation." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0007/MQ34335.pdf.

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33

Ayyagari, Suhaas Bhargava. "ARTIFICIAL NEURAL NETWORK BASED FAULT LOCATION FOR TRANSMISSION LINES." UKnowledge, 2011. http://uknowledge.uky.edu/gradschool_theses/657.

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This thesis focuses on detecting, classifying and locating faults on electric power transmission lines. Fault detection, fault classification and fault location have been achieved by using artificial neural networks. Feedforward networks have been employed along with backpropagation algorithm for each of the three phases in the Fault location process. Analysis on neural networks with varying number of hidden layers and neurons per hidden layer has been provided to validate the choice of the neural networks in each step. Simulation results have been provided to demonstrate that artificial neural network based methods are efficient in locating faults on transmission lines and achieve satisfactory performances.
34

勞偉籌 and Wai-chau Edward Lo. "Servo control of robotic manipulator with artificial neural network." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31235128.

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35

Benchebra, Dalil. "Artificial neural network-based control for process tomography applications." Thesis, Manchester Metropolitan University, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.502437.

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Electronic Capacitance Tomography systems have proved to be extremely useful in non-invasive measurement for industrial applications. While considerable research effort has been focused on the development and refinement of measurement techniques based on ECT, use of ECT for realtime control has not attracted the same extent of research effort. This work demonstrated that a novel combination of ECT systems and Artificial Neural Networks (ANNs) can be used to control of highly nonlinear industrial systems continuously as demonstrated by the implementation of a neural network-based inverse controller for the MMU laboratory flow. rig conveying the polypropylene pellets. The nature of the flow ofpneumatically conveyed pellets is highly nonlinear which tends to lead to the formation of dunes, necessitating an increase of air velocity to the maximum to clear the dunes, and hence requiring large control energy. If the air velocity can be controlled such that the pellet flow is maintained at a constant rate without the build up of dunes, energy usage associated with such processes can be considerably reduced. One of the main problems in the control of the pneumatic pellet flow system is the difficulty in building good models of the nonlinear dynamics of the system. In this work, ANNs are used to initially build and validate a model of the forward dynamics of the system and then to develop an inverse model of the plant. This inverse model is implemented as a Controller to maintain constant pellet flow and to clear dunes as quickly as possible. Results are obtained from a laboratory flow rig interfaced to a Virtual Instrument Tomographic Measurement System and controlled using dedicated hardware with software implemented in LabView and Matlab. The NN-based controller was highly effective in maintaining a steady pellet flow over long durations of time even in the presence of mass flow disturbances. The results presented in this work showed that a NN-based controller can eliminate energy wastage by automatically clearing dunes as and when they form while maintaining the air velocity at a minimum value necessary to keep the pellet flow homogeneous. Serial and Parallel ECT systems were used in the imaging and control experiments. The additional information obtained by the high imaging rates of the parallel ECT system was used to improve the performance of the controller for long term operations. Hierarchical Self-Organising Maps were also shown to be highly effective in improving the accuracy of the images obtained using the standard Linear Back Projection algorithm for application in ECT-based systems.
36

Trigo, Ricardo M. "Improving meteorological downscaling methods with artificial neural network models." Thesis, University of East Anglia, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327283.

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37

Elhewy, Ahmed. "Probabilistic analysis of composite structures using artificial neural network." Thesis, University of Newcastle Upon Tyne, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.413045.

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38

Lai, Jia-Rui, and 賴家瑞. "Forecasting seasonal time series a neural network approach." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/24637066498895294235.

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Анотація:
碩士
國立政治大學
應用數學研究所
81
We investigate the effectiveness of neural networks for predicting the future behavior of seasonal time series. Utilizing the training set constructed properly, we can train the network who can be used to predict the future of seasonal time series. A shifting-learning method is also employed in order to obtained a better forecasting performance. The quarterly imports of goods and services of Taiwan between the first quarter of 1968 and the fourth quarter of 1990 are studied in the research. The series are contaminated with outliers, which will increase the difficulty of forecasting. Empirical results exhibit that neural networks model free approach have better prediction performance than the classical Box-Jenkins approach, even the series are contaminated with outliers.
39

Hwang, Yih-Shyan, and 黃議賢. "Password Authentication Using Artificial Neural Network." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/00101971263020082688.

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Анотація:
碩士
國立中興大學
應用數學研究所
82
In this dissertation, a password authentication scheme based on artificial neural network model with modified perceptron algorithm and a strong cryptographic operation such as DES(data encryption standard) is proposed. Because of parallel computing characteristics of artificial neural network, the scheme can quickly and efficiently respond to any login attempt. Thus, it is suitable for real-time service. Moreover, each user is completely free to choose his own identifier and password. Because those identifiers and passwords in the system are combined together, any illegal modification by the intruder to the weight matrices in the artificial neural network will influence the others and can easily be detected. Furthermore, after a new user is inserted into the system, it needs only to add few terms of the former weight matrices. Therefore, our scheme is suitable for practical implementation.
40

Su, chutin, and 蘇祝鼎. "Artificial Neural Network for Dipole Localization." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/64838032357715825842.

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Анотація:
碩士
國立交通大學
控制工程系
85
In this thesis, we use the neural networks to deal with the problem of dipole localization. We aim at estimating location, orientation, and moment strength of a single dipole which induces epilepsy in human brain. The inverseproblem is a highly nonlinear approximation process. We applied current dipolemodel to generate the brain electrical potential distribution on the scalp. The dipole and its corresponding brain potentials were used as training patternsfor the neural networks. A neural network trained to learn correspondence of dipoles to brain potential distribution can be used to estimate the dipole''slocation, orientation, and moment strength. It will be useful for clinicalapplications. In this reasearch, we investigatedthe cppability of neural network in dipole localization. The performance of the neural network depends on region of dipole localization andorientation of dipole moment. we also studied the effect of noise interferencefor the performance of neural network. We found that the accuracy of dipole localization decreased as the signal-to-noise ratio was poor. In addition, we proposed a model of hybrid network . Compared with the conventional multi-layer perceptrons network, the hybri d network indeed requires less training time and achieves better localization results. It might be a feasible neural network model for dipole localization.
41

Chen, You-Yu, and 陳宥諭. "DOA Estimation with Artificial Neural Network." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/2pxvzy.

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Анотація:
碩士
國立交通大學
電信工程研究所
107
A uniform linear array can receive multiple unequal power signals coming from different direction-of-arrival (DOA). This thesis considers DOA estimation with artificial neural network (NN). Conventional NN approaches are not effective for the unequal-power scenario. Also, the computational complexity is very high. Incorporating signal processing techniques, we propose two NNs to solve the problems. The first NN divides the estimation range into sectors, and consists of a spatial filter and a classifier. With a rotation operation, a spatial filter and a classifier can be used for all sectors, significantly reducing the training time and computational complexity. The second NN uses the same sector-based processing structure. However, the spatial filter is replaced with a power detector. With a frequency-domain nulling operation, only a power detector and a classifier are needed for all sectors. The computational complexity of the second NN can be further reduced. Simulation results show that the performance of the proposed NNs can outperform the well-known MUSIC algorithm under low SNR. Also, the computational complexity can also be lower than that of MUSIC.
42

Zeng, Shi-Ran, and 曾世任. "Artificial Neural Network for Image Recognition." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/87588825955623867932.

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Анотація:
碩士
國立高雄海洋科技大學
電訊工程研究所
99
Biometrics is a common topic. In this field, neural network is a common machine learning algorithm, and it has been applied to many fields. Recently, support vector machines (referred to as SVM) which is based on statistical learning theory catches the most attention. It is because SVM has the better recognition capability and faster calculation speed than the general neural networks; furthermore, it does not have the situation of over-learning. There are many researches proving that SVM has good performance of recognition in the open literature. Probabilistic neural network (referred to as PNN) is a kind of neural network based on Bayesian decision theory, and it belongs to the feedforward network architecture. PNN is highly regarded due to its short training time, and also, it does not have the iterative process. In this thesis, we apply in human face recognition and Traditional Chinese handwriting recognition. Most researches use the public face databases in human face recognition. For example, they are ORL, Yale, INDIAN, etc. Thus, we use data source both from ORL and the database created by ourselves in this study. In handwriting, the database was made of 20 persons handwriting in Traditional Chinese. In this study, we consider individual handwriting habits use different quantitative methods to explore the feasibility of using handwriting recognition as an identification identity. The experimental results show that the recognition rate by using SVM and ORL is 96%, while the recognition rate for our database is 92%(Block Background) and 80%(White Background) respectively. In Traditional Chinese handwriting, the best rate of using SVM to recognize is 75%, while the best rate for PNN is 80%.
43

Lin, I.-Chih, and 林奕志. "Infrared Face Recognition Using Artificial Neural Network." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/70053617787203072670.

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Анотація:
碩士
國立高雄第一科技大學
電腦與通訊工程所
92
This research aims at the construction of an infrared face recognition system. Although the development of the visible face recognition system has been developed for many years, as well as many other recognition algorithms, the performance is not satisfactory, due to several environmental distracters, such as light, the instruments, which bring about the problems of feature extraction. However, as far as this infrared face recognition system is concerned, based on the heat radiation of the human body, the final extracted information is the actual temperature which would not be affected by light, for example. And that is one of the advantages of the use of infrared images, which draws increasing attention for further studies. The employment of the infrared face recognition system which would not be affected by light is proven successfully. Also, the infrared image of different targets cannot be counterfeited. Hence, the performance of the infrared face recognition is regarded more effective than that of the visible face recognition system. In practice, due to the high expense of the infrared machine plus the serious noise problem and its poor resolution, the infrared face recognition system is currently under further research and development. In this thesis, the employment of a new technique in the infrared face recognition field is studied, with the comparison and contrast between the performances of the new analysis and the traditional analysis. The first part of this thesis is to introduce the methods for the image pre-process and the face clip. In the face clip, two methods to clip the two different kinds of the face images from the background are illustrated. Some adjustments are in particular made for the clipped face images as the preparation for the next discussion. Secondly, three kinds of analysis methods in the feature extraction stage are executed. Because of the resolution limits of the infrared machine, even though the temperature accuracy of the machine can achieve hundredth, there are still several problems in the facial feature extraction. In other words, the visible face recognition, used for the homely facial feature extraction, is not as practical for infrared image. With different targets, the facial features of the persons may not be successfully extracted as expected. So, as far as feature extraction is concerned, the entire face image is discussed other than the local feature extraction. The third part is the construction of the recognition system. In this thesis, the “Plastic Perceptron” to classify different people is used. In the traditional neural network, if the user wants to add the new extracted facial information into the recognition system, the entire neural network should be retrained. But now, it is not necessary when employing the Plastic Perceptron. Therefore, the Plastic Perceptron is regarded as more suitable for face recognition.
44

Chang, Chern Yuan, and 張承遠. "Solving Linear Systems with Artificial Neural Network." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/30583228224322399023.

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45

Lin, Tz-tsau, and 林子超. "Structural Damage Detection using Artificial Neural Network." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/61054947437243824323.

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Анотація:
碩士
國立成功大學
航空太空工程學系
85
This thesis presents an approach based on the artificial neural network to detect damages in a structure. By using the modal information of a structure before and after damage, we construct an artificial neural network model.The neural network is trained by examples which simulate various cases of structural damage using the finite element model of the structural system. The objective is to detect possible damage, including both extent and location,in the structure. Validity of the proposed approach is confirmed by using simulated examples in which the effect of noise and incomplete mode are included.
46

Byun, Jong-Min. "Artificial neural network system for array beamformer." 1991. http://catalog.hathitrust.org/api/volumes/oclc/24487340.html.

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Thesis (M.S.)--University of Wisconsin--Madison, 1991.
Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 21-22).
47

吳國嘉. "Artificial Neural Network for Plastic Injection Mold." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/nt6746.

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Анотація:
碩士
建國科技大學
自動化工程系暨機電光系統研究所
106
It is due to the requirements for fast and precision for plastics. A series of design and setting parameters is important for clients and productivity programming. This study employed software, MODEX 3D, to simulate flow to evaluate a design with multi-pore. The Taguchi method make use of a table including a few factors including crew material temperature, injection pressure, packing pressure, packing time and mold temperature. Through the optimization of the above factors and modeling, the procedure was established.
48

Liu, Shin-Hsu, and 劉時旭. "Artificial Neural Network on Court Auction Houses." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/52612806418017603818.

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Анотація:
碩士
國立中興大學
土木工程學系所
100
Auction houses are the real estate of the Foreclosure. Generally speaking, the auction price is lower than general market price. In recent years, the real estate price getting higher and higher, and it attracts a large number of bidders entering the foreclosure market. For example, in 2010, the market statistics number for foreclosure is 60630, the amount of money is NT.134.4 billion . In recent years, auction houses had been subjected to people''s attention. But the information for auction houses is still extremely lacking. Due to the real estate market is an imperfectly competitive market, the proceeds of the information is often not be complete. The price can only be estimated by some fundamental concepts. By using the information to estimate a more accurate price will help reducing the risk for buyers. Therefore, this study use Artificial Neural Network to establish a model to estimate auction houses .By collecting cases of auction houses, we select the finest information as input variables, including: (1)the width of facing road (2)numbers of facing road (3) population density, (4)delivered by the court or not, (5) property rights, (6) current assessed land value, (7) land possession, (8) floor area, (9) bid price, (10) how many times the auction, etc. Analyze and review the relevant input variables Improvement Amendments through the training and the parameters of the artificial neural network learning, we can estimate the price. In particular, the population density is often that can’t be effectively achieved. In this study, we use the number of chain convenience store within a radius of 500 meters as an analysis of indicators. This innovative and facilitate accurate input variables, significantly increasing the accuracy of the research results. The research results show that: the artificial neural network is indeed available fast, accurate forecast of the result, so we recommend that this is good for assessment of auction houses.
49

Horng, Yu Jing, and 洪毓鈞. "Process Optimization via an Artificial Neural Network." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/61356944221656412222.

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Анотація:
碩士
逢甲大學
化學工程研究所
83
In this thesis, we consider the issue of applying neural network to the process optimization problem and robust controller design problem. The objective function of unconstrainted optimization problem can be mapped on to the energy function of the artificail neural network(ANN)in a direct way, and the network will find the minimum by obeying its own dynamics. For the optimization problem with constraints, we used the augmented Lagrange multiplier method to transform problem into a problem in which a single unconstrainted function is minimized, then we found the answer by the same step. As for the robust controller design problem, we applied the idea of Rotstein et al. to formulate the robust characteristic polynomial assignment problem as an optimization problem subject to linear constraints with uncertainty, at last we attained the controller by the same methods of optimization function with constraints. In order to prove the ability of artificial neural network and the affection of parameters, we tested several examples, the result was satisfactory and robust controller was better than the result of literature.
50

WANG, YOU-REN, and 王祐人. "Artificial neural network for digits pattern recognition." Thesis, 1991. http://ndltd.ncl.edu.tw/handle/09177770124098150633.

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