CNN Based Automatic Speed and Steering Control System Using Matlab

Acharya, G. Prasad; Krishna, P. Sai; Reddy, K Srikar; Sanjana, S.; Shashank, M. Shvejan

doi:10.1149/10701.13155ecst

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…Machine learning models are widely employed in various tasks in the previous studies [6][7][8]. The following section moves on to the specific experiments.…”

Section: Model Buildingmentioning

confidence: 99%

Application of Machine Learning in Recommendation Algorithms

Han¹

2022

HSET

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With the development of technology, the importance of recommendation algorithms in online transactions is gradually increasing. The development of machine learning is essential to improve the performance of recommendation algorithms. Therefore, a suitable model is urgently needed for recommendation algorithms. In order to evaluate the performance of classical machine learning algorithms against newer machine learning algorithms, four models were selected, namely Decision Tree model, Random Forest model, Gradient Boosting Decision Tree model and XGBoost model. They were subjected to regression analysis on the same dataset, and the final scores were derived from the four parameters r2_score, MSE, MAE, and expected variance. The article selects a set of recommendation dataset from Amazon platform and processes the noisy data in the dataset. The data is processed by three methods, namely direct deletion, character digitisation and natural language processing, to obtain a valid dataset of 19, 676 items, and divided into training and prediction sets according to 7:3. Next, the models included in the sklearn library in PYTHON were used for regression analysis to obtain the performance scores of each model. The Decision Tree model had the lowest score of 0.70584 and the Gradient Boosting Decision Tree model had the highest score of 0.85281. In addition, in general, the Decision Tree model scored much worse than the other three models, while the other three models scored more similarly.

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“…Machine learning models are widely employed in various tasks in the previous studies [6][7][8]. The following section moves on to the specific experiments.…”

Section: Model Buildingmentioning

confidence: 99%

Application of Machine Learning in Recommendation Algorithms

Han¹

2022

HSET

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“…country to improve learning efficiency, speed up learning progress, save a lot of valuable time to use in understanding and applying the basic concept of new knowledge, and give full play to the potential of college students [6,7].…”

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confidence: 99%

Exploration and Practice of Matlab Course in Undergraduate Student of Science and Technology

2022

CURTM

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In order to improve the teaching quality of MATLAB course, this paper expounds the necessity for teaching MATLAB course in undergrade students of science and technology, and specially analyses the problems faced by the junior grade students when they are studying. Through the exploration and practice of MATALAB course teaching, this paper probes into the structure of course content, teaching content and teaching mode, and points out the concrete measures to teach MATLAB course in the junior students ofundergraduate. Necessity of MATLAB Course in Undergraduate StudentsMATLAB is a large-scale comprehensive software for scientific and engineering computing that integrates numerical calculation, symbolic calculation and visualization developed by MathWorks of the United States. It has a friendly working platform and programming environment, a simple and easy to use programming language, a strong scientific computing data processing capability, a color graphics processing function, a widely used module collection toolbox, and a practical program interface and platform, which are widely used in all walks of life. Because MATLAB is suitable for multi-subject and multi-work platform, it has the characteristics of powerful function, friendly interface, natural language and strong openness, it is recognized as accurate and reliable scientific standard software in international academic circle [1,2,3]. In the early 1990s, MATLAB became the preferred software for science majors in American, British, Canadian and Australian universities. In the design research unit and industrial department, MATLAB is considered as the first choice software tool for efficient research and development. Such as National Instruments'signal measurement and analysis software LABview, Cadence's signal and communication analysis and design software SPW, etc., are directly built on the MATLAB or supported by MATLAB[4]. In American and European universities, advanced courses such as linear algebra, numerical analysis, mathematical statistics, optimization methods, digital signal processing, electro-technical and electronic technology, modelling and dynamic system simulation all take MATLAB as a basic teaching content. At present, among the non-computer majors in science and engineering colleges in developed countries, the most popular programming languages are not C, BASIC, FORTRAN, but MATLAB. In our country, only master, doctor and some scientific researchers use MATLAB language at present, but the students of this specialty use less, most students have not used MATLAB [5]. Therefore, it is of great significance and function to popularize and apply MATLAB software to college students of science and technology in our Curriculum and Teaching Methodology (2022) Clausius Scientific Press, Canada

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CNN Based Automatic Speed and Steering Control System Using Matlab

Cited by 2 publications

References 9 publications

Application of Machine Learning in Recommendation Algorithms

Application of Machine Learning in Recommendation Algorithms

Exploration and Practice of Matlab Course in Undergraduate Student of Science and Technology

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