Neural network applied

The aim of this research was to examine if a visual based training method could improve badminton player's decision making and in game performance. This research comprises a collection of research problems relating 10 visual based training, digital learning and general tau theory in relation 10 badminton.

183p runthenight05 01-03-2023 7 3   Download

Intrusion Detection (ID) is one of the active branches in network security research field. Many technologies, such as neural networks, fuzzy logic and genetic algorithms have been applied in intrusion detection and the results are varied. In this thesis, an Artificial Immune System (AIS) based intrusion detection is explored. AIS is a bio-inspired computing paradigm that has been applied in many different areas including intrusion detection.

74p runthenight07 01-03-2023 6 2   Download

Research Aims: The thesis aims to develop deep neural networks for analyzing security data. These techniques improve the accuracy of machine learning-based models applied in NAD. Therefore, the thesis attempts to address the above challenging problems in NAD using models and techniques in deep neural networks. Specifically, the following problems are studied.

128p armyofthedead 23-06-2021 12 2   Download

The techniques of supervised ones are applied to the data domain in order to have a comparison between the evaluated system of POSSUM and the advantage of Neural network. The comparisons are based on the rate of mortality and morbidity of patients. The outcome set of unsupervised learning techniques is compared to the results of supervised ones.

8p tamynhan8 04-11-2020 19 1   Download

Pricing and guessing the right prices are vital for both hosts and renters on homesharing plat-form from internet based companies. To contribute the growing interest and immense literatureon applying Artificial Intelligence on predicting rental prices, this paper attempts to build ma-chine learning models for that purpose using the Luxstay listings in Hanoi. R2 score is used as the main criterion for the model performance and the results show that Extreme GradientBoostings (XGB) is the model with the best performance with R2= 0.

44p hoanghung9393 28-08-2020 11 2   Download

Trong bài báo này chúng tôi đề xuất các mạng nơron SOM có giám sát, gồm S-SOM và S-SOM+ áp dụng cho bài toán phân lớp. Các mạng này được cải tiến từ các mô hình SOM không giám sát và có giám sát đã được đề xuất bởi Kohonen và các tác giả khác. Sau đó, chúng tôi tiếp tục đề xuất các mô hình SOM có giám sát phân tầng cải tiến từ S-SOM và S-SOM+, gọi là HS-SOM và HS-SOM+.

14p dieutringuyen 07-06-2017 28 1   Download

A comparison between three methods applied to parallel robot control namely: Computed torque controller, sliding mode control and sliding mode control using neural networks is presented in this paper. The simulation results show that PD control method is only accurate when model parameters are precisely identified.

11p dieutringuyen 07-06-2017 49 5   Download

EURASIP Journal on Applied Signal Processing 2003:12, 1229–1237 c 2003 Hindawi Publishing Corporation Nonlinear System Identification Using Neural Networks Trained with Natural Gradient Descent Mohamed Ibnkahla Electrical and Computer Engineering Department, Queen’s University, Kingston, Ontario, Canada K7L 3N6 Email: mohamed.ibnkahla@ece.queensu.ca Received 13 December 2002 and in revised form 17 May 2003 We use natural gradient (NG) learning neural networks (NNs) for modeling and identifying nonlinear systems with memory.

9p sting12 10-03-2012 42 5   Download

EURASIP Journal on Applied Signal Processing 2003:9, 890–901 c 2003 Hindawi Publishing Corporation An Efficient Feature Extraction Method with Pseudo-Zernike Moment in RBF Neural Network-Based Human Face Recognition System Javad Haddadnia Engineering Department, Tarbiat Moallem University of Sabzevar, Sabzevar, Khorasan 397, Iran Email: haddadnia@sttu.ac.ir Majid Ahmadi Electrical and Computer Engineering Department, University of Windsor, Windsor, Ontario, Canada N9B 3P4 Email: ahmadi@uwindsor.

12p sting12 10-03-2012 37 6   Download

EURASIP Journal on Applied Signal Processing 2003:3, 276–286 c 2003 Hindawi Publishing Corporation Robust Clustering of Acoustic Emission Signals Using Neural Networks and Signal Subspace Projections Vahid Emamian Department of Electrical & Computer Engineering, University of Minnesota, 200 Union St. SE, Minneapolis, MN 55455, USA Email: emamian@ieee.org Mostafa Kaveh Department of Electrical & Computer Engineering, University of Minnesota, 200 Union St. SE, Minneapolis, MN 55455, USA Email: mos@ece.umn.edu Ahmed H.

11p sting12 10-03-2012 54 6   Download

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Applying Novel Time-Frequency Moments Singular Value Decomposition Method and Artificial Neural Networks for Ballistocardiography

9p dauphong20 10-03-2012 40 4   Download

Assume that gi (x) = 1 (hence gk (x) = 0, k = i), update the expert i based on output error. Update gating network so that gi (x) is even closer to unity. Alternatively, a batch training method can be adopted: 1. Apply a clustering algorithm to cluster the set of training samples into n clusters. Use the membership information to train the gating network. 2. Assign each cluster to an expert module and train the corresponding expert module. 3. Fine-tune the performance using gradient-based learning. Note that the function of the gating network is to partition the feature...

20p longtuyenthon 26-01-2010 108 9   Download