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3rd International conference on intelligent Systems and Advanced Computing Sciences, ISACS 2019

作者： Ouanan, Hamid Abdelwahed, El Hassan National School of Applied Sciences Sultan Moulay Slimane University Beni Mellal Morocco CSEHS Mohammed VI Polytechnic University Marrakesh Morocco

ISBN: (纸本)9781728148137

Recently, Image processing (IP) and Machine learning (ML) algorithms have been successfully used in a wide variety of industry sectors. In this paper, we first provide mining engineers with the state of the art about IP and ML applications in the mining industry. furthermore, we propose a real time application for froth image analysis in the context of mineral processing. Finally, we propose some future directions, including suggestions on mining data collection and development of an exploration tool based on IP and ML algorithms by taking advantage of cloud computing technology to analyze geoscience data in order identify target areas with high prospectively potential. © 2019 IEEE.

关键词： Machine learning

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From Manual to Machine: How AI is Redefining Web Scraping for Superior Efficiency: A Literature Review 3

From Manual to Machine: How AI is Redefining Web Scraping fo...

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3rd International conference on Communication, Control, and intelligent Systems, CCIS 2024

作者： Ayuso, Enrique Dumfeh Brogya, Maame Serwah Kumar Ahlawat, Vinay Sain, Mangal Dongseo University Dept. of Computer Engineering Busan Korea Republic of Gla University Dept. of Electronics & Communication Mathura India

ISBN: (纸本)9798331528201

Web Scraping involves the use of bots for the purpose of extracting data from the online web. To extract such data, the web scraper must conduct at least 3 different steps, i.e., collect the necessary links from the web, extract data using the provided links, and save the information in a neatly organized CSV file or database. However, traditional methods to accomplish these steps have faced many difficulties, such as anti-scraping measures and website changes. To tackle these difficulties and to accomplish the steps in a more rapid yet advanced way, Artificial Intelligence (AI) can be utilized. As of mid-2024, the rapid development and improvement of AI has resulted in its integration into many businesses and educational institutions. The current state of AI is remarkably advanced that it can be integrated in about any field and sector available. In this paper, the researcher defined the term Web Scraping, Artificial Intelligence, Natural Language Processing, and Machine learning, explained the use of AI in Web Scraping including its importance and potential, and the understanding of ethical web scraping practices. This literature review indicated that the integrated use of AI improves the performance of Web Scraping compared to traditional methods. © 2024 IEEE.

关键词： Adversarial machine learning

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Research on intelligent Frequency Regulation Capability Evaluation Technology for Coal-Fired Units Based on Autonomous Controllable PLC 3

Research on Intelligent Frequency Regulation Capability Eval...

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2022 3rd International conference on Smart Grid and Energy Engineering, SGEE 2022

作者： Sun, Yuanming Zhang, Tengyu Zhao, Xin Sun, Zhonghua Nie, Zhe Datang Harbin First Co-generation Power Plant Heilongjiang Harbin150078 China Datang Northeast Power Test & Research Institute Co. Ltd. Jilin Changchun130102 China

The generation frequency of grid-connected units determines the power supply reliability of the grid and primary frequency regulation, as the first guarantee to stabilize the grid frequency is affected by the category of generating units and operation mode and lacks systematic real-time optimization and monitoring means. This paper takes a 300MW sub-critical heating unit as the research object, and researches, and analyzes three aspects of signal homologation, multi-dimensional optimization, and intelligent decision-making to establish the evaluation model of the primary frequency regulation capability of the unit. The evaluation accuracy of the assessment model reaches 83%, develops the control platform based on autonomous controllable PLC, realizes intelligent dynamic control and the replacement of traditional optimization technology means, also improves the qualification rate of primary frequency regulation by about 23.2%. © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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Fast learning automaton solution to the keyboard optimization problem

Fast learning automaton solution to the keyboard optimizatio...

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Proceedings of the 3rd International conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems - IEA/AIE 90

作者： Oommen, B.J. Valiveti, R.S. Zgierski, J. Carleton Univ Ottawa Canada

ISBN: (纸本)0897913728

Let A be a finite alphabet, and H be a finite dictionary of words formed from the letters of this alphabet. In a conventional keyboard typically each key of the keyboard is assigned a unique symbol chosen from the alphabet. We consider the problem of assigning more than one symbol of the alphabet A to the same key on the keyboard. Let Ci be a subset of A. Every time a character in Ci is to be represented, the keyboard represents it using the digit (i.e. the index) 'i'. In a keyboard of this form, since multiple symbols of the alphabet A have the same representation, the representations of all the (distinct) words in the dictionary H need not be unique. A useful measure of the effectiveness of a particular keyboard is the number of words of H which are mapped to the same encoded form (i.e. they collide). This metric will be termed the ambiguity associated with the keyboard. The problem we study is one of optimally assigning the symbols of the alphabet to the keys of a given keyboard with a view to minimize the resulting ambiguity. The problem as stated above is proven to be NP-hard. This naturally leads us to seek fast and approximate solutions to the optimization problem on hand. After presenting the only reported solution to the problem, we report a fast learning automaton-based solution to this problem. Experimental results demonstrating the power of this solution have also been presented.

关键词： learning Systems

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News Classification System using Machine learning Approach 3

News Classification System using Machine Learning Approach

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3rd International conference on Advances in Computing, Communication Control and Networking, ICAC3N 2021

作者： Singh, Yash Veer Naithani, Piyush Ansari, Parvez Agnihotri, Pragya ABES Engineering College Department of Information Technology Ghaziabad India

ISBN: (纸本)9781665438117

As more and more sources publish a large amount of news on the Internet every day, it is necessary to categorize news articles so that users can effectively obtain information. The amount of information from print and digital media is huge, which leads to intelligent analysis of large amounts of data, all of which are large amounts of unclassified data, stored together will not give results, so we can make some decisions, so we need categorize messages and use different algorithms to assign multiple tags based on their category. Text message classification using machine learning is the process of automatically classifying message information according to predefined tags, which are based on their content and whose accuracy comes from the training message records. The research paper analyzed many algorithms to build the system, such as Naive Bayes, SVM and neural networks for classification based on machine learning algorithms. Articles are classified according to business, entertainment, politics, sports, technology and other fields. In this way, with the help of the news classification system, users can find news articles they are interested in, which saves time and eliminates news overhead. © 2021 IEEE.

关键词： Support vector machines

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Influence of aircraft's maneuver flight performance parameters on within visual range air combat effectiveness 3

Influence of aircraft's maneuver flight performance paramete...

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3rd International conference on Unmanned Systems, ICUS 2020

作者： Zhen-Ning, Zhang Jia-Ning, W.E.I. Zhen-Biao, T.U. Fei-Fei, L.I. Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728180250

The fighter's war ability is closely related to its maneuver ability. The maneuver measurement index of the new generation fighter changed greatly compared to the traditional rules. This essay firstly introduced the modern fighter's maneuver performance quantized index. According to the built simulation system, take two typical third generation fighter models as the confront sides, built fuzzy control intelligent decision model based on the genetic algorithm, simulated the one-to-one air combat confront process. Under such circumstances, adjusted the maneuver flight performance parameters reasonable and got the confront simulation results, then analyzed and evaluated the influence of the parameterad justed within visual range air combat effectiveness, which provided reference significance to air combat flight's original design and maneuver flight performance parameter optimization. © 2020 IEEE.

关键词： Fuzzy control

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A data-driven approach towards fast economic dispatch in integrated electricity and natural gas system

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ENERGY REPORTS 2023年 9卷 894-903页

作者： Zhang, Bin Xu, Xiao Chen, Zhe Hu, Weihao Aalborg Univ Dept Energy Technol DK-9220 Aalborg Denmark Sichuan Univ Coll Elect Engn Chengdu 610065 Peoples R China Univ Elect Sci & Technol China Sch Mech & Elect Engn Chengdu 610000 Peoples R China

Effective economic dispatch for the integrated energy system (IES) can improve energy efficiency and promote renewable energy accommodation. Tradition IES economic dispatch are based on model-based methods that rely on accurate system parameters and uncertainty prediction. This paper proposes a data-driven fast economic dispatch method based on deep reinforcement learning (DRL) in an integrated electricity and natural gas system (IEGS). Unlike other DRL-based studies that spend a lot of computation time to calculate power flow, we employ DNNs to learn the complex nonlinear relationship existing in the IEGS, namely IEGSNet. Then, the economic dispatch problem is formulated as a Markov decision process, and solved by the soft actor-critic (SAC) algorithm. Simulation results illustrate that the proposed method achieves the similar operation cost to the tradition DRL-based dispatch method, but takes almost one tenth of the training time. Additionally, the computation time of the proposed method for 10-day dataset is at least two orders of magnitudes shorter that the model-based optimization algorithm. (c) 2023 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Integrated energy system Energy dispatch Data-driven Deep reinforcement learning Neural network

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Wordle data analysis and prediction based on SIR infectious disease model and Grey Wolf optimization algorithm 3

Wordle data analysis and prediction based on SIR infectious ...

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3rd International conference on Applied Mathematics, Modelling, and intelligent Computing, CAMMIC 2023

作者： Pu, Yongjun Zhang, Long Hu, Hengdi Lin, Caizhi Zhou, Bingyi Chengdu Technological University Sichuan Chengdu China Chengdu University of Technology Sichuan Chengdu China

ISBN: (数字)9781510667617

ISBN: (纸本)9781510667600

Wordle is a free web crossword that has exploded into global popularity in 2022, and it has a lot to offer in terms of gameplay. In order to explore the reasons for the popularity of Wordle games, the bionic SIR Epidemic model is used to predict the number of Wordle players and analyze the reasons for the change of the number of players in combination with the mode of game transmission. Information entropy is used to process Wordle word data in the past, and the relationship between word attributes and players' completion rate is analyzed. A more accurate model is then built to predict the specific distribution of the number of times players in Wordle correctly guess the word. The input data set was constructed from the word attributes that mainly affect Wordle players, and the multi-output prediction model was built based on the bionic encircle tracking method of GWO. The mathematical model above is used to systematically predict the future trend of Wordle. © 2023 SPIE.

关键词： Forecasting

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Research on the Construction of Planning and Design System of intelligent Networked Automobile Proving Ground 3

Research on the Construction of Planning and Design System o...

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3rd International conference on Machine learning and Big Data Analytics for IoT Security and Privacy, SPIoT2023

作者： Hu, Qingqing Wu, Luyin Hu, Lan Liu, Peng You, Huaqiong School of Art and Media Chongqing Metropolitan College of Science and Technology Chongqing China Department of Road Design Chongqing Tongcheng Engineering Consulting Design Co. Ltd Chongqing China

Based on the actual project, combined with the goal of intellectualization and networking, this study discusses the planning and design system and its application value of site selection, general layout planning, supporting buildings, test roads and site landscape. In the process of studying the planning and design, the planning and design of various parts of intelligent networked automobile proving ground are analyzed and summarized, and the design module library is established, the design data is analyzed, the design standards are formulated, the cost control is realized through design optimization, the evaluation mechanism of the planning scheme is established, and the planning and design system of intelligent networked automobile proving ground is constructed, which provides technical reference for the design of intelligent networked automobile infrastructure, with a view to providing practical application value for the planning and design of intelligent networked automobile proving ground. It can not only provide technical support for the construction of intelligent networked automobile infrastructure, but also provide feasible and economical reference for related enterprises in the construction of test sites, and has important promotion and application prospects. © 2023 Elsevier B.V.. All rights reserved.

关键词： Automobile proving grounds

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Artificial Intelligence Strategies and Their Impact on Economic Stability: Conceptual Framework 3

Artificial Intelligence Strategies and Their Impact on Econo...

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3rd European conference on the Impact of Artificial Intelligence and Robotics (ECIAIR)

作者： Serova, Elena Natl Res Univ Higher Sch Econ St Petersburg Russia

ISBN: (纸本)9781914587238

Understanding the exceptional role of intelligent technologies and systems in the new digital economy has given rise to a new technological race - artificial intelligence. In emerging markets, artificial intelligence and intelligent technologies are, in fact, an integral part of cutting-edge management systems. They add to the globalization of business by providing quick access to employees, customers, and partners worldwide, as well as coordinating global interaction between companies at different stages of the value chain. It does not mean that intelligent technologies and systems simply increase the efficiency of a company's operations;they can be considered as a key intangible asset. The AI strategy is defined as a set of coordinated policies that have a clear objective of maximizing the potential benefits and minimizing the potential costs of AI for the economy and society. In the past few years, two dozen countries have launched their national strategies in the field of artificial intelligence. Many countries have already developed their AI strategy at the official level during the last 3 years. The main goal of this paper is the analysis of the emerging market multinational enterprises (EMNEs) AI strategies to support the emergent economy and identify key AI strategies development directions. The research is based on the analysis of large volumes of information, the author's own experience, and literature review that includes the latest findings in this field. Research Methodology includes a systematic approach, comparative analysis, case-study, and modeling. The problem the author considers here is: How can we reduce the impact of risks and uncertainty on the economic stability with the help of AI and how the emerging market multinational enterprises (EMNEs)' AI Strategies have already been successfully using the AI Strategies in the past fifteen years? The findings of the research are based on providing a framework for assessing the role of EMNEs' AI strate

关键词： artificial intelligence machine learning emerging market multinational enterprises artificial intelligence strategy artificial intelligence policy multinational enterprises artificial strategies framework

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