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作者： Rudraraju, Sanjay Varma Rochester Institute of Technology

学位级别：M.S.

Within artificial intelligence, the sub-field of multi-agent systems studies the foundations of agent interactions and strategic behavior. Two-sided matching is one of the most fundamental problems in this field with applications in matching residents to hospitals, kidney donors to receivers and students to high schools. The earliest algorithm that solved this problem is the Gale-Shapley algorithm which guarantees a stable matching based on the preferences of both sides but has a drawback of favoring one side over the other, that is, proposers always get their most optimal stable partner. We consider the design and analysis of gender-neutral stable matching algorithms where the proposing side from both sides is randomly chosen thereby giving an equal probability for both sides to get their most optimal stable partner (ex-ante). Later, we focus on investigating if an agent can exhibit strategic behavior i.e., whether it is possible for an agent to manipulate so that he/she improve the partner obtained when on the proposed side while retaining the partner obtained when on the proposing side. The results obtained showed that for some manipulation algorithms, agents can still manipulate the outcome even when the decision of which side is proposing is unknown. Also, empirical evaluations were performed to understand and solidify the results.

关键词： Multiagent systems Matching theory computer algorithms

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Towards Effective Network Intrusion Detection: A Hybrid Model Integrating Gini Index and GBDT with PSO

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JOURNAL OF SENSORS 2018年第3-26期2018卷

作者： Li, Longjie Yu, Yang Bai, Shenshen Cheng, Jianjun Chen, Xiaoyun Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Gansu Peoples R China China Informat Technol Secur Evaluat Ctr Beijing 100085 Peoples R China Lanzhou Vocat Tech Coll Dept Elect & Informat Engn Lanzhou 730070 Gansu Peoples R China

In order to protect computing systems from malicious attacks, network intrusion detection systems have become an important part in the security infrastructure. Recently, hybrid models that integrating several machine learning techniques have captured more attention of researchers. In this paper, a novel hybrid model was proposed with the purpose of detecting network intrusion effectively. In the proposed model, Gini index is used to select the optimal subset of features, the gradient boosted decision tree (GBDT) algorithm is adopted to detect network attacks, and the particle swarm optimization (PSO) algorithm is utilized to optimize the parameters of GBDT. The performance of the proposed model is experimentally evaluated in terms of accuracy, detection rate, precision, F1-score, and false alarm rate using the NSL-KDD dataset. Experimental results show that the proposed model is superior to the compared methods.

关键词： Malware (computer software) computer systems Machine learning computer algorithms computer architecture Particle swarm optimization

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Using High-Order Prior Belief Predictions in Hierarchical Temporal Memory for Streaming Anomaly Detection

Using High-Order Prior Belief Predictions in Hierarchical Te...

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作者： Kutt, Brody Rochester Institute of Technology

学位级别：M.S.

Autonomous streaming anomaly detection can have a significant impact in any domain where continuous, real-time data is common. Often in these domains, datasets are too large or complex to hand label. algorithms that require expensive global training procedures and large training datasets impose strict demands on data and are accordingly not fit to scale to real-time applications that are noisy and dynamic. Unsupervised algorithms that learn continuously like humans therefore boast increased applicability to these real-world scenarios. Hierarchical Temporal Memory (HTM) is a biologically constrained theory of machine intelligence inspired by the structure, activity, organization and interaction of pyramidal neurons in the neocortex of the primate brain. At the core of HTM are spatio-temporal learning algorithms that store, learn, recall and predict temporal sequences in an unsupervised and continuous fashion to meet the demands of real-time tasks. Unlike traditional machine learning and deep learning encompassed by the act of complex functional approximation, HTM with the surrounding proposed framework does not require any offline training procedures, any massive stores of training data, any data labels, it does not catastrophically forget previously learned information and it need only make one pass through the temporal data. Proposed in this thesis is an algorithmic framework built upon HTM for intelligent streaming anomaly detection. Unseen in earlier streaming anomaly detection work, the proposed framework uses high-order prior belief predictions in time in the effort to increase the fault tolerance and complex temporal anomaly detection capabilities of the underlying time-series model. Experimental results suggest that the framework when built upon HTM redefines state-of-the-art performance in a popular streaming anomaly benchmark. Comparative results with and without the framework on several third-party datasets collected from real-world scenarios also show a c

关键词： Memory management (computer science) Machine learning Pattern perception--Data processing computer algorithms

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Robust Smooth Sliding-Mode-Based Controller with Fixed-Time Convergence for Missiles considering Aerodynamic Uncertainty

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INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING 2018年第Pt.2期2018卷 12-12页

作者： Yun, Yuhang Guo, Jie Tang, Shengjing Beijing Inst Technol Sch Aerosp Engn Beijing 100081 Peoples R China

This paper designed a smooth fixed-time-convergent sliding mode controller for a missile flight system considering aerodynamic uncertainties. Fixed-time convergence theory is incorporated with the sliding mode control technique to ensure that the system tracks desired commands within uniform bounded time under different initial conditions. Unlike previous terminal sliding mode approaches, not only is the bound of settling time independent of initial state, indicating that performance metrics like convergence rate can be predicted beforehand, but the control input is designed to be smooth based on adaptive estimations and some mathematical results without introducing any discontinuous items like the signum function, which avoids the problem of chattering consequently. A cascade control structure is employed with the derived control algorithm, and therein, the control input signal is obtained. Finally, a number of simulations are carried out and demonstrate the effectiveness of the designed controller.

关键词： missiles Performance metrics missile flight Controllers Sliding mode control input Signum function computer algorithms INITIAL CONDITIONS Converge input signal Sliding mode technique

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PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2018年第1期2018卷 6094685-6094685页

作者： Chen, Shuangqing Liu, Yang Wei, Lixin Guan, Bing Northeast Petr Univ Sch Petr Engn Daqing 163318 Peoples R China

Particle swarm optimization (PSO) and fireworks algorithm (FWA) are two recently developed optimization methods which have been applied in various areas due to their simplicity and efficiency. However, when being applied to high-dimensional optimization problems, PSO algorithm may be trapped in the local optima owing to the lack of powerful global exploration capability, and fireworks algorithm is difficult to converge in some cases because of its relatively low local exploitation efficiency for noncore fireworks. In this paper, a hybrid algorithm called PS-FW is presented, in which the modified operators of FWA are embedded into the solving process of PSO. In the iteration process, the abandonment and supplement mechanism is adopted to balance the exploration and exploitation ability of PS-FW, and the modified explosion operator and the novel mutation operator are proposed to speed up the global convergence and to avoid prematurity. To verify the performance of the proposed PS-FW algorithm, 22 high-dimensional benchmark functions have been employed, and it is compared with PSO, FWA, stdPSO, CPSO, CLPSO, FIPS, Frankenstein, and ALWPSO algorithms. Results show that the PS-FW algorithm is an efficient, robust, and fast converging optimization method for solving global optimization problems.

关键词： PARTICLE swarm optimization MATHEMATICAL optimization computer algorithms

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On the reliability of acoustic annotations and automatic detections of Antarctic blue whale calls under different acoustic conditions

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JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2018年第2期144卷 740-754页

作者： Leroy, Emmanuelle C. Thomisch, Karolin Royer, Jean-Yves Boebel, Olaf Van Opzeeland, Ilse CNRS F-29280 Plouzane France Univ Brest Inst Univ Europeen Mer Lab Geosci Ocean F-29280 Plouzane France Alfred Wegener Inst Helmholtz Zentrum Polar & Meeresforsch Ocean Acoust Lab D-27570 Bremerhaven Germany Carl von Ossietzky Univ Oldenburg Helmholtz Inst Funct Marine Biodivers D-26129 Oldenburg Germany

Evaluation of the performance of computer-based algorithms to automatically detect mammalian vocalizations often relies on comparisons between detector outputs and a reference data set, generally obtained by manual annotation of acoustic recordings. To explore the reproducibility of these annotations, inter-and intra-analyst variability in manually annotated Antarctic blue whale (ABW) Z-calls are investigated by two analysts in acoustic data from two ocean basins representing different scenarios in terms of call abundance and background noise. Manual annotations exhibit strong inter-and intra-analyst variability, with less than 50% agreement between analysts. This variability is mainly caused by the difficulty of reliably and reproducibly distinguishing single calls in an ABW chorus made of overlaying distant calls. Furthermore, the performance of two automated detectors, based on spectrogram correlation or subspace-detection strategy, is evaluated by comparing detector output to a "conservative" manually annotated reference data set, which comprises only analysts' matching events. This study highlights the need for a standardized approach for human annotations and automatic detections, including a quantitative description of their performance, to improve the comparability of acoustic data, which is particularly relevant in the context of collaborative approaches in collecting and analyzing large passive acoustic data sets. (C) 2018 Acoustical Society of America.

关键词： SOUND production by animals BLUE whale ACOUSTICS NOISE computer algorithms

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Sinc-Windowing and Multiple Correlation Coefficients Improve SSVEP Recognition Based on Canonical Correlation Analysis

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2018年第1期2018卷 1-11页

作者： Mondini, Valeria Mangia, Anna Lisa Talevi, Luca Cappello, Angelo Univ Bologna Dept Elect Elect & Informat Engn DEI Cesena Italy

Canonical Correlation Analysis (CCA) is an increasingly used approach in the field of Steady-State Visually Evoked Potential (SSVEP) recognition. The efficacy of the method has been widely proven, and several variations have been proposed. However, most CCA variations tend to complicate the method, usually requiring additional user training or increasing computational load. Taking simple procedures and low computational costs may be, however, a relevant aspect, especially in view of low-cost and high-portability devices. In addition, it would be desirable that the proposed variations are as general and modular as possible to facilitate the translation of results to different algorithms and setups. In this work, we evaluated the impact of two simple, modular variations of the classical CCA method. The variations involved (i) the number of canonical correlations used for classification and (ii) the inclusion of a prefiltering step by means of sinc-windowing. We tested ten volunteers in a 4-class SSVEP setup. Both variations significantly improved classification accuracy when they were used separately or in conjunction and led to accuracy increments up to 7-8% on average and peak of 25-30%. Additionally, variations had no (variation (i)) or minimal (variation (ii)) impact on the number of algorithm steps required for each classification. Given the modular nature of the proposed variations and their positive impact on classification accuracy, they might be easily included in the design of CCA-based algorithms that are even different from ours.

关键词： CANONICAL correlation (Statistics) EVOKED potentials (Electrophysiology) computer users COMPUTATIONAL complexity computer algorithms

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Active Vibration Control of the Sting Used in Wind Tunnel: Comparison of Three Control algorithms

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SHOCK AND VIBRATION 2018年第Pt.9期2018卷 1905049.1-1905049.10页

作者： Shen, Xing Dai, Yuke Chen, Mingxuan Zhang, Lei Yu, Li Nanjing Univ Aeronaut & Astronaut State Key Lab Mech & Control Mech Struct Nanjing 210016 Jiangsu Peoples R China Nanjing Chenguang Grp Corp Ltd Nanjing 210006 Jiangsu Peoples R China China Aerodynam Res & Dev Ctr Mianyang 621000 Peoples R China

In wind tunnel tests, cantilever stings are often used as model-mount in order to reduce flow interference on experimental data. In this case, however, large-amplitude vibration and low-frequency vibration are easily produced on the system, which indicates the potential hazards of gaining inaccurate data and even damaging the structure. This paper details three algorithms, respectively, Classical PD Algorithm, Artificial Neural Network PID (NNPID), and Linear Quadratic Regulator (LQR) Optimal Control Algorithm, which can realize active vibration control of sting used in wind tunnel. 'I he hardware platform of the first-order vibration damping system based on piezoelectric structure is set up and the real-time control software is designed to verify the feasibility and practicability of the algorithms. While the PD algorithm is the most common method in engineering, the results show that all the algorithms can achieve the purpose of over 80% reduction, and the last two algorithms perform even better. Besides, self-tuning is realized in NMI), and with the help of the Observer/Kalman Filter Identification (OKID), LQR optimal control algorithm can make the control effort as small as possible. The paper proves the superiority of NNPID and LQR algorithms and can be an available reference for vibration control of wind tunnel system.

关键词： tunnel Wind algorithms wind tunnels Piezoelectric devices computer algorithms vibration control linear quadratic regulators low frequency vibration

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Correlation Assisted Strong Uncorrelating Transform Complex Common Spatial Patterns for Spatially Distant Channel Data

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2018年第1期2018卷 1-9页

作者： Kim, Youngjoo You, Jiwoo Lee, Heejun Lee, Seung Min Park, Cheolsoo Kwangwoon Univ Dept Comp Engn Seoul 01897 South Korea Kookmin Univ Sch Elect Engn Coll Creat Engn Seoul 02707 South Korea

The Strong Uncorrelating Transform Complex Common Spatial Patterns (SUTCCSP) algorithm, designed for multichannel data analysis, has a limitation on keeping the correlation information among channels during the simultaneous diagonalization process of the covariance and pseudocovariance matrices. This paper focuses on the importance of preserving the correlation information among multichannel data and proposes the correlation assisted SUTCCSP (CASUT) algorithm to address this issue. The performance of the proposed algorithm was demonstrated by classifying the motor imagery electroencephalogram (EEG) dataset. The features were first extracted using CSP algorithms including the proposed method, and then the random forest classifier was utilized for the classification. Experiments using CASUT yielded an average classification accuracy of 78.10 (%), which significantly outperformed those of original CSP, Complex Common Spatial Patterns (CCSP), and SUTCCSP with. p-values less than 0.01, tested by the Wilcoxon signed rank test.

关键词： MULTICHANNEL communication DATA analysis SPATIAL analysis (Statistics) CORRELATION (Statistics) ELECTROENCEPHALOGRAPHY computer algorithms

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Optimization of Magnetic-Grating-Like Stroke-Sensing Cylinder Based on Response Quality Evaluation Algorithm

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JOURNAL OF SENSORS 2018年第3-11期2018卷 7046390-7046390页

作者： Guo, Yanqing Liu, Lu Fu, Yongling Li, Chuangchuang Guo, Liang North Univ China Shanxi Key Lab Adv Mfg Technol 3 Xueyuan Rd Taiyuan Shanxi Peoples R China North Univ China Sch Mech & Power Engn 3 Xueyuan Rd Taiyuan Shanxi Peoples R China Beihang Univ Sch Mech Engn & Automat 37 Xueyuan Rd Beijing Peoples R China

The measurement of hydraulic cylinder displacement has been addressed from different fields. The detection principle of magnetic grating is able to realize the high integration and accuracy. In this paper, a signal response quality evaluation algorithm for devising and optimizing a high-accuracy displacement measuring system is proposed. On the basic of signal response quality evaluation method, structure variables are optimized to enhance the working performance. By defining the parameters, an optimum structure cylinder prototype is made and tested to provide better estimates. Experimental results on working characteristic are presented to verify the effectiveness of the optimized structure. The efficiency of the proposed signal response quality evaluation function is therefore demonstrated through the working performance.

关键词： Hydraulic cylinders Displacement (Mechanics) Accuracy Magnetic field effects computer algorithms

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