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检索条件"主题词=inference algorithms"

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The N-R method of acquiring multi-step reasoning production rules based on NN

The N-R method of acquiring multi-step reasoning production ...

引用

International Conference on Neural Networks

作者： Li Yi Shi Hongbao Department of Computer Science Xi''an Jiaotong University Xi'an Shaanxi China

ISBN: (纸本)0780332105

We present the N-R method of acquiring multi-step reasoning production rules based on a neural network (NN), so as to simulate one of the ways human beings learn-acquiring hierarchically structured knowledge from non-structured training samples. This method is composed of a characteristic NN structure to model the corresponding learning algorithm, and the transform algorithm which converts a trained NN to a reasoning network (RN), from which production rules can be obtained easily.

关键词： Neural networks Dairy products Knowledge acquisition Humans Machine learning algorithms inference algorithms Production systems Animals Computer science Computational modeling

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Design method for a novel human simulation intelligent controller

Design method for a novel human simulation intelligent contr...

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IEEE International Conference on Intelligent Processing Systems, ICIPS

作者： Yaqing Tu Department of Automatic Engineering Logistical Engineering University Chongqing China

ISBN: (纸本)0780342534

Based on the model of human simulation intelligent controller (HSIC) presented briefly, a detailed algorithm is described for servo system control by using the method of HSIC. Simulation results obtained prove the good performance of the control algorithm. HSIC is a multilevel hierarchical structure information processing system with three levels. The direct control level executes real time control. The parameter correction level automatically readjusts control mode parameters in the direct control level. The task adjustment level selects, modifies and even generates the characteristics model, inference rules, control and decision mode and parameters in direct control and parameter correction levels. All three levels combined form a unit controller with the structure of a typical high order production system.

关键词： Design methodology Humans Automatic control Automatic generation control Servomechanisms Control system synthesis inference algorithms Information processing Character generation Control systems

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Improved Intrusion Detection System Using Fuzzy Logic for Detecting Anamoly and Misuse Type of Attacks

Improved Intrusion Detection System Using Fuzzy Logic for De...

引用

International Conference of Soft Computing and Pattern Recognition (SOCPAR)

作者： Bharanidharan Shanmugam Norbik Bashah Idris Centre for Advanced Software Engineering UTM International Campus Kuala Lumpur Malaysia

Currently available intrusion detection systems focus mainly on determining uncharacteristic system events in distributed networks using signature based approach. Due to its limitation of finding novel attacks, we propose a hybrid model based on improved fuzzy and data mining techniques, which can detect both misuse and anomaly attacks. The aim of our research is to reduce the amount of data retained for processing i.e., attribute selection process and also to improve the detection rate of the existing IDS using data mining technique. We then use improved Kuok fuzzy data mining algorithm, which in turn a modified version of APRIORI algorithm, for implementing fuzzy rules, which allows us to construct if-then rules that reflect common ways of describing security attacks. We applied fuzzy inference engine using mamdani inference mechanism with three variable inputs for faster decision making. The proposed model has been tested and benchmarked against DARPA 1999 data set for its efficiency and also tested against the ¿live¿ networking environment inside the campus and the results has been discussed.

关键词： Intrusion detection Fuzzy logic Data mining Software engineering Turing machines inference algorithms Data security Testing Information security Artificial intelligence

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Physics-Guided Diffusion Models for Inverse Design

Physics-Guided Diffusion Models for Inverse Design

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Dongjin Seo Soobin Um Jong Chul Ye Haejun Chung Hanyang University Seoul Korea Republic of Korea Advanced Institute of Science and Technology Daejeon Korea Republic of

We propose a new technology that utilizes the adjoint gradient and exploits the score-based property of diffusion models to optimize the structure of optical devices.

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

We propose a new technology that utilizes the adjoint gradient and exploits the score-based property of diffusion models to optimize the structure of optical devices.

关键词： Performance evaluation Optical losses Laser theory Optical design Diffusion models Laser modes inference algorithms

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DDM: Study Of Deer Detection And Movement Using Deep Learning Techniques

DDM: Study Of Deer Detection And Movement Using Deep Learnin...

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International Symposium on Autonomous Decentralized Systems (ISADAS)

作者： Md Jawad Siddique Khaled R. Ahmed Computer Science SIUC Carbondale Illinois

Deer Vehicle Collisions (DVCs) is a major concern in road safety that results in loss of human life, properties and wildlife. DVCs mostly occurs during the fourth quarter of the year when deer are more active andless attentive. DVCs are increasing due to the increase in number of vehicles and the absence of intelligent highway safety and alert systems. One of the most challenging issues is to detect deer and its movement on roadways during both day and nighttime to mitigate DVCs. Thus, this paper proposed a deer detection and movement, DDM technique to automate DVCs mitigation system The DDM combines computer vision, artificial intelligent methods with deep learning techniques. DDM includes two main deep learning algorithms 1) one-stage deep learning algorithm based on Yolov5 that generates a detection model (DM) to detect deer and 2) deep learning algorithm developed by python toolkit DeepLabCut to generate movement model (MM) for detecting the movement of the deer. The proposed method can detect deer with 99. 7% precision and usingDeepLabCuttoolkit on the detected deer we can ascertain if the deer is moving or static with an inference speed of $\theta$. 29s.

关键词： Deep learning Road transportation Computer vision Computational modeling Wildlife Road safety inference algorithms

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Combination of online Clustering and Q-value based genetic reinforcement learning for fuzzy network design

Combination of online Clustering and Q-value based genetic r...

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International Joint Conference on Neural Networks (IJCNN)

作者： Chia-Feng Juang Chun-Feng Lu Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Department of Electrical Engineering Chung Chou Institute of Technology Changhua Taiwan

ISBN: (纸本)0780378989

This paper proposes a combination of on-line Clustering and Q-value based Genetic Algorithm learning scheme for Fuzzy network design (CQGAF) with reinforcements. The CQGAF fulfills GA based fuzzy network design under reinforcement learning environment where only weak reinforcement signals such as "success" and "failure" are available. In CQGAF, there are no fuzzy rules initially. They are generated automatically. The precondition part of a fuzzy network is online constructed by an aligned clustering-based approach. Simultaneously, the consequent part is designed by Q-value based genetic reinforcement learning. In CQGAF, evolution is performed immediately after the end of one trial in contrast to general GA where many trials are performed before evolution. The feasibility of CQGAF is demonstrated through simulations in cart-pole balancing problems with only binary reinforcement signals.

关键词： Learning Fuzzy systems Genetic algorithms Algorithm design and analysis Signal design State estimation Fuzzy sets Clustering algorithms inference algorithms Stochastic processes

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Design of a dynamically reconfigurable, integrated, parallel vision system

Design of a dynamically reconfigurable, integrated, parallel...

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International Conference on Pattern Recognition

作者： A. Samal University of Nebraska Lincoln Lincolnshire NE USA

The main focus in parallel computer vision has so far been the design and analysis of parallel algorithms to perform individual operations. While it clearly is necessary and useful, it is not the ultimate goal. The goal is to design and implement a parallel vision system which integrates all the parallel vision modules easily and efficiently. A framework for building a parallel vision system is presented. The necessary and desirable features of such a system are identified. An initial design which incorporates these features is given.< >

关键词： Machine vision Computer vision Algorithm design and analysis Buildings Parallel algorithms Application software inference algorithms Object recognition Layout Service robots

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Poisson-Gamma Dynamical Systems 16

Poisson-Gamma Dynamical Systems

引用

Annual Conference on Neural Information Processing Systems

作者： Aaron Schein Mingyuan Zhou Hanna Wallach College of Information and Computer Sciences University of Massachusetts Amherst Amherst MA 01003 McCombs School of Business The University of Texas at Austin Austin TX 78712 Microsoft Research New York 641 Avenue of the Americas New York NY 10011

ISBN: (纸本)9781510838819

We introduce a new dynamical system for sequentially observed multivariate count data. This model is based on the gamma-Poisson construction-a natural choice for count data-and relies on a novel Bayesian nonparametric prior that ties and shrinks the model parameters, thus avoiding overfitting. We present an efficient MCMC inference algorithm that advances recent work on augmentation schemes for inference in negative binomial models. Finally, we demonstrate the model's inductive bias using a variety of real-world data sets, showing that it exhibits superior predictive performance over other models and infers highly interpretable latent structure.

关键词： DYNAMICAL SYSTEMS Tie Dataset Binomial Models inference algorithms model parameters

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Tuning and optimization at Brookhaven and Argonne: results of recent experiments

Tuning and optimization at Brookhaven and Argonne: results o...

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IEEE Conference on Particle Accelerator

作者： W. Klein C. Stern M. Kroupa R. Westervelt G. Luger E. Olsson Vista Control Systems Inc. USA University of New Mexico USA

Vista Control Systems Inc. is developing a portable system for intelligent accelerator control. Our system is general purpose and has been designed to be reused at multiple accelerator facilities. This portability arises from the hierarchical object-oriented nature of the architecture. The control system employs a multi-level organization in which knowledge based inferencing is used to dynamically configure a variety of optimization and control algorithms. We discuss results from recent beamline tuning tests at the Brookhaven National Laboratory ATF and the ATLAS facility at Argonne. Results are analyzed along a number of dimensions, including portability, performance as benchmarked against human tuning, adaptive behavior, noise handling, integration of control subsystems, and support for rapid knowledge capture and utilization.

关键词： Control systems Intelligent systems Intelligent control inference algorithms Laboratories Performance analysis Benchmark testing Humans Programmable control Adaptive control

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Dynamic Multi-relational Chinese Restaurant Process for Analyzing Influences on Users in Social Media

Dynamic Multi-relational Chinese Restaurant Process for Anal...

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IEEE International Conference on Data Mining (ICDM)

作者： Himabindu Lakkaraju Indrajit Bhattacharya Chiranjib Bhattacharyya IBM Research India Stanford University IBM Research India Indian Institute of Science Indian Institute of Science

We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.

关键词： Media Mathematical model Data models inference algorithms Equations Analytical models Algorithm design and analysis

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