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检索条件"主题词=software algorithms"

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A K-means Improved CTGAN Oversampling Method for Data Imbalance Problem

A K-means Improved CTGAN Oversampling Method for Data Imbala...

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IEEE International Conference on software Quality, Reliability and Security (QRS)

作者： Chunsheng An Jingtong Sun Yifeng Wang Qingjie Wei CQUPT. Chongqing Engineering Research Center of Software Quality Assurance Testing and Assessment Chongqing China Seaquam Secondary Delta Canada

ISBN: (纸本)9781665458146

CTGAN is a tabular data synthesis method for privacy preservation, which is used in this paper for data imbalance problem. This paper proposes a method for dealing with imbalanced data sets that combines K-means clustering and CTGAN to address the imbalanced distribution of minority class examples that result from oversampling with CTGAN. By conducting experiments with the LightGBM algorithm on home loan and online shopping datasets, it is demonstrated that the CTGAN method achieves superior learning results in f1-score and G-mean metrics compared to the interpolation-based oversampling technique represented by SMOTE. The preceding results indicate that by applying the method described in this paper to handle an imbalanced dataset, one can obtain a dataset with more examples, a more uniform distribution, and less overfitting while still satisfying the original dataset's probability distribution.

关键词： Measurement Data privacy Conferences software algorithms Clustering algorithms software quality Probability distribution

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Establishment and Algorithm Analysis of The Simulated Electronic Circuit model Based on The Neural Network

Establishment and Algorithm Analysis of The Simulated Electr...

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Electronic Information Technology and Smart Agriculture (ICEITSA), International Conference on

作者： Siyuan Peng Chengdu University of Technology College of Mechanical and Electrical Engineering Chengdu China

ISBN: (纸本)9781665413015

With the rapid development of science and technology and social economy, neural network, as the main research direction of modern intelligent system, has played a positive role in medical devices, intelligent robots, automatic control and other fields. In this paper, when studying the neural network as the core of analog electronic circuit model, MOS transistor is used to build the corresponding basic circuit model, and the relevant algorithm is introduced and analyzed. Pspice is chosen as the development platform. Compared with digital circuit, analog circuit can be completed with fewer components, while MOS transistor can facilitate integrated circuit, and the neural network algorithm code needs to be written in Matlab software simulation. The final results show that the neural network as the core of the analog electronic circuit model can not only obtain more algorithm functions, but also improve the integration of neural network, so it belongs to the main direction of modern integrated circuit innovation development.

关键词： Analytical models Technological innovation MOSFET software algorithms SPICE Mathematical models software

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Comparing Grover’s Quantum Search Algorithm with Classical Algorithm on Solving Satisfiability Problem

Comparing Grover’s Quantum Search Algorithm with Classical ...

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IEEE Integrated STEM Education Conference (ISEC)

作者： Runqian Wang Princeton International School of Math and Science USA

ISBN: (纸本)9781665413848

The emergence of quantum computing provides us the possibility of solving tasks that might take years classically in just a few minutes. For certain problems, quantum computing exhibits quantum supremacy, meaning that the quantum solution runs exponentially faster than classical algorithms and is able to completely take over classical computers. This high efficiency of quantum computing comes not only from the hardware but also the software, quantum algorithms. The algorithms utilize the qubits to make calculations in order to fulfill specific tasks with the lowest time complexity possible. One such algorithm is named the Grover’s algorithm, which is able to perform database search in $\mathcal{O}(\sqrt{N})$, and it runs much faster than the traditional algorithm that takes $\mathcal{O}(N)$ time to solve the same task. For example, when the task is to find the even integers from N integers, traditional computation will need to run through all of the N integers one by one, making at least N steps of calculation, while by using Grover’s algorithm only around $\sqrt{N}$ calculations are needed. This exponential speed-up makes Grover’s algorithm one of the most important quantum algorithms. Grover’s algorithm has a wide application in many fields and is able to improve the time complexity exponentially. One task that can be solved using Grover’s algorithm is the satisfiability problem. This type of problem asks the computer to find a set of values (commonly true or false) for several variables such that they satisfy certain constraints. We use k-SAT problems to refer to satisfiability problems with k boolean variables to be determined. Grover’s algorithm can effectively solve the k-SAT problem by performing the database search on $2 ^{N}$ possible states of the variables. The algorithm’s square root optimization on searching helps to improve the efficiency of this solution significantly. Furthermore, this optimization of Grover’s algorithm may play a more important role

关键词： Computers Quantum algorithm Databases software algorithms Qubit Search problems software

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Implementation of Power Battery Voltage Fault Diagnosis System Based on Improved Shannon Entropy Algorithm

Implementation of Power Battery Voltage Fault Diagnosis Syst...

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IEEE International Conference on Networking, Sensing and Control

作者： Weidong Fang Yiting Jiang Hao Lv Fujian Key Laboratory of Automotive Electronics and Electric Drive Fujian University of Technology Fuzhou China

ISBN: (纸本)9781665440493

Nowadays, electric vehicles have become one of the most promising new products. The research on the faults in the power battery system can effectively diagnose the faults in the power battery system, predict the occurrence of faults, and improve the service life of the power battery system. This paper uses Matlab / Simulink to simulate the sensor data acquisition system. It builds our own database on software to receive the data sent by MATLAB, and sends the data in the format of can message, so as to build the joint simulation system of CANoe and MATLAB. This enables data exchange between the *** connecting Jetson Nano with CANoe software and big data platform onenet, the principle of Shannon entropy algorithm is studied, and the improved Shannon entropy is realized through software programming. The big data platform displays the single cell voltage data obtained by Jetson nano and the results of single cell voltage through Shannon entropy algorithm. The experimental results show that Shannon entropy can predict the voltage undervoltage fault of single cell 52 seconds in advance.

关键词： Fault diagnosis software packages software algorithms Big Data Predictive models Prediction algorithms Entropy

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Formant set as a main parameter for recognizing vowels of the Uzbek language

Formant set as a main parameter for recognizing vowels of th...

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International Conference on Information Science and Communications Technologies (ICISCT)

作者： Malika Abdullaeva Ilyos Khujayorov Mannon Ochilov Computer Systems Tashkent University of Information technologies named after Muhammad Al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9781665432597

The article highlights the applications of the algorithm for speech signal recognition using a formant set. A description of the formation of the speech signal by the human articulating apparatus is given. The influence of the human speech apparatus organs on the formant parameter is also described. The Linear Prediction Method (LPC) is used for determining the formant set in order to identify the peaks on the spectral diagram of the original signal. The paper presents the formant set for the Uzbek vowels pronounced by several speakers of the same age category with different genders after cochlear surgery. Based on the formant set graphs are constructed and classification problems over them are solved using machine learning algorithms such as K-Nearest Neighbors, Random Forest, Support Vector Machines. The scientific paper consists of a comparative analysis of the three main classification methods on such a priority parameter as recognition accuracy in order to simplify the process of speech signal recognition. The results of the classification revealed that the recognition of Uzbek vowel letters on the basis of the formant set is achieved using KNN and is 95%.

关键词： Machine learning algorithms software algorithms Surgery Support vector machine classification Speech recognition Prediction methods Prediction algorithms

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Simulation and verification of pedestrians in asymmetric funnel-shaped bottlenecks based on Pathfinder

Simulation and verification of pedestrians in asymmetric fun...

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Urban Engineering and Management Science (ICUEMS), International Conference on

作者： Weibin Ma Zhiwei Wang Hongliang Pan State Key Laboratory for Track Technology of High-speed Railway Railway Construction Institute Beijing China University of Science and Technology of China Hefei China

Bottlenecks are common in pedestrian facilities and prone to congestion. An observation experiment was conducted at the asymmetric bottleneck to study pedestrians' movement. We constructed the simulation by Pathfinder to make comparison and further study the influence of bottleneck angles by simulation results. It is found Pathfinder can simulate the evacuation at the asymmetric bottleneck based on similar efficiency and congestion. However, the difference exists in the trajectory and speed fluctuation for the simulation. Adding the funnel-shaped zone before the exit in the asymmetric bottleneck can improve the evacuation efficiency and reduce congestion and the angle 45° performs the best according to the simulation. These results have a reference for the improvement of evacuation efficiency in the asymmetric bottleneck and reflect the effectiveness and problems of the simulation software Pathfinder.

关键词： Fluctuations Simulation software algorithms software Data models Trajectory Data mining

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Estimations of vehicle driving state and road friction coefficient based on High-degree cubature Kalman filter of distributed drive electric vehicles *

Estimations of vehicle driving state and road friction coeff...

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Conference on Vehicle Control and Intelligence (CVCI)

作者： Yongle Feng Bin Zhang Rongyun Zhang Peicheng Shi Zhen Wang Chenglong Zhou School of Mechanical Engineering Anhui Polytechnic University Wuhu China

ISBN: (纸本)9781665408486

It is necessary to improve the estimated accuracy of vehicle driving state and road friction coefficient for distributed drive electric vehicles. This paper proposed an estimation algorithm of vehicle driving state and road friction coefficient based on high-degree cubature Kalman filter. First, a 3 degrees-of-freedom nonlinear vehicle dynamics model with Dugoff's tyre friction model is established; Then, a high-degree cubature Kalman filter-based algorithm for estimating vehicle driving state was designed, and the relationship between vehicle state data and road friction coefficient was used to estimate the road friction coefficient; Finally, a distributed drive electric vehicles model was built with Carsim/Simulink software for validating the estimation algorithm. The results show that the estimation accuracy of the algorithm based on high-degree cubature Kalman filter is higher than that of the algorithm based on traditional cubature Kalman filter.

关键词： Friction Roads Heuristic algorithms Vehicle driving software algorithms Estimation Drives

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YOLOv5 based Open-Source UAV for Human Detection during Search And Rescue (SAR)

YOLOv5 based Open-Source UAV for Human Detection during Sear...

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International Conference on Advanced Computer Control, ICACC

作者： M S Sruthi Manal Jaleel Poovathingal V N Nandana S Lakshmi Mohamed Samshad V S Sudeesh Govt. Engineering College Thrissur Thrissur India ICFOSS Thiruvanathapuram India

ISBN: (纸本)9781665439206

Floods and earthquakes are among the most frequently occurring natural disasters. They account for high mortality rates due to their rapidness and uncertainty of occurrence. Inundated lands require a quick response for rapid evacuation, arresting fatalities, and consequential economic losses. People tend to seek shelter at dry and open lands at times of calamity. The manual Search and Rescue (SAR) operations have their shortcomings due to the difficulties in identifying the human presence. It requires a longer time for evacuation and therefore increased mortalities. This paper proposes a quadcopter for real-time monitoring of isolated places and automatically detecting stranded humans during floods using image processing techniques at affordable rates. Live video streaming is possible with a camera and a video transmission system attached to the quadcopter. The rescue centers automatically receive the location of humans in case of human detection. Our model integrates an Open-Source autopilot system model, APM 2.8 multicopter flight controller that efficiently stabilizes the flight, and a YOLOv5 object tracking convolutional neural network algorithm for faster detection of human beings. The model is trained using a dedicated dataset of more than 1000 images and attains 0.954 mAP. We have developed a drone using open-source hardware and software tools, conducted test flights to check its stability and the efficiency of the object detection algorithm. We also conducted a mini-survey of one of the most flood-prone areas of Thrissur district in Kerala, using Mission Planner open-source software to evaluate how quickly our drone can assess the entire area. The aim is to save more human lives by quick and efficient aerial assessment in the most cost-efficient manner.

关键词： Uncertainty software algorithms Streaming media Cameras Real-time systems Hardware Floods

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Multi-Sensor Measurements Fusion for Passive Target Tracking in Underwater

Multi-Sensor Measurements Fusion for Passive Target Tracking...

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Advances in Computing, Communication Control and Networking (ICAC3N), International Conference on

作者： S. Koteswara Rao Kausar Jahan Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur Andhra Pradesh India

ISBN: (纸本)9781665438124

The pivot goal of estimation algorithms is to generate information with a quality higher than that of raw measurements available and to extract the information that can be obtained indirectly from the available measurements. To fulfill this aim, the measurements from multiple sensors are combined to get a more accurate and reliable estimate of the target. In this research work, measurements from five multiple sensors are combined to get different motion parameters of the desired target. The sub-optimal filter, Unscented Kalman filter is considered for the performance analysis of the algorithm. The simulation is carried in MATLAB software using the Monte-Carlo simulation method for better analysis of the results.

关键词： Target tracking Sonar measurements software algorithms Sonar Signal processing algorithms Position measurement software

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Evaluation of Design Optimisation Techniques in Structural Framing

Evaluation of Design Optimisation Techniques in Structural F...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Luke Briese Timothy Mark Gregory Navid Mohajer Matthew Watson Shady Mohamed Saeid Nahavandi Institute for Intelligent Systems Research and Innovation Deakin University Australia

ISBN: (纸本)9781665442084

Structural design optimisation can significantly contribute to the identification of the best shape and geometry of a structure that results in lighter, stronger, and more affordable to manufacture materials for both large scale manufacturing and one-off bespoke performance components. Being both modern (evolutionary) and classic optimisation methods have had extensive focus and application in this field, an evaluation study on the performance of these methods has not been reported. This study reports a systematic comparison of the modern and classic optimisation approaches for a benchmark design optimisation problem. One algorithm will be a classic gradient-based optimisation, the second being a general Genetic Algorithm (GA) type optimisation. The results of two optimisation methods will be compared through the application of Finite Element Analysis (FEA) to evaluate both the performance of each algorithm and the real word translation of their effectiveness. The outcomes reveal that, although the gradient-based method shows better statistical results, GA can result in a superior minimum FoS of 3.5 satisfying the requirements for most common structural design applications.

关键词： Systematics Welding software algorithms Optimization methods Benchmark testing software Finite element analysis

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