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intelligent optimal control model of selection pressure for rapid culture of aerobic granular sludge based on machine learning and simulated annealing algorithm

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BIORESOURCE TECHNOLOGY 2024年 413卷 131509页

作者： Liu, Zhe Lei, Jie Cheng, Linshan Yang, Rushuo Yang, Zhuangzhuang Shi, Bingrui Wang, Jiaxuan Zhang, Aining Liu, Yongjun Xian Univ Architecture & Technol Sch Environm & Municipal Engn Yan Ta Rd 13 Xian 710055 Peoples R China Xian Univ Architecture & Technol Key Lab Northwest Water Resource Environm & Ecol Minist Educ Xian 710055 Peoples R China Xian Univ Sci & Technol Sch Architecture & Civil Engn Yan Ta Rd 58 Xian 710054 Peoples R China

Aerobic Granular Sludge (AGS) has advantages over Activated sludge (AS) but faces challenges with long granulation periods. In this study, a novel grey-box model is devised to optimize the cultivation of AGS to shorten the formation time. This model is based on an existing white-box model. The modeling process starts with the application of four sensitivity analysis methods to assess the 12 model metrics selected. Subsequently, 12 prediction models were constructed by combining the six Machine learning (ML) algorithms and integrated algorithms, with the best performance selected (R-2 = 0.98). Finally, an AGS selection pressure planning model was designed in conjunction with a simulated annealing (SA) algorithm to guide AGS training. The results demonstrate that AGS formation could be achieved within four days under the model's optimal control. Therefore, the establishment of this model provides a new technique for the cultivation of AGS.

关键词： White-box model Black-box model Grey-box model intelligent algorithms Planning model

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Stability Prediction Techniques for Electric Power Systems based on Identification Models and Gramians

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IFAC-PapersOnLine 2019年第13期52卷 481-485页

作者： Bakhtadze, N. Yadykin, I. V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Science Moscow Russia 65 Profsoyuznaya Moscow117997 Russia

The methods for developing predictive models in control systems and decision-making support for nonlinear non-stationary objects are proposed. The methods are based on the application of associative search procedure to virtual model identification as well as Gramian techniques. The associative search methods use intelligent process knowledge analysis. The knowledge base is created and extended in real-time process operation. intelligent algorithms are offered for predicting power plant dynamics in optimization tasks. Gramian technique of stability analysis for discrete system is used for investigating linear virtual model stability. It is shown that the bilinear Lyapunov equation solutions can be calculated as an infinite sum of the matrix quadratic forms made up by the products of the Faddeev matrices obtained by decomposing of linear subsystem dynamic matrix resolvents. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Predictive analytics Decision making Electric power system stability Knowledge based systems Lyapunov functions Matrix algebra Number theory Wavelet analysis Associative Search Decision making support Gramians Identification model intelligent algorithms Knowledge base Non stationary objects Process identification

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Research on Robot Machining Path Planning Technology for NURBS Surface

Research on Robot Machining Path Planning Technology for NUR...

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International Conference on Mechanical Design and Simulation (MDS)

作者： Miao, Pei Bai, Yuewei Pang, Changtao Shanghai Polytech Univ Sch Resources & Environm Engn Shanghai 201209 Peoples R China Beijing Inst Aeronaut Precis Machinery Beijing 100076 Peoples R China

ISBN: (纸本)9781510655263;9781510655256

This paper studies the surface machining path representation based on NURBS and its key technologies of path planning, analyzes the advantages and disadvantages of various path planning algorithms for NURBS surfaces, and finds that the current NURBS surface machining path planning algorithms mainly consider geometric constraints, while There is less correlation analysis on the index of machined surface roughness, so it is necessary to combine intelligent algorithms and other technologies in the future to better solve practical engineering problems. Path planning algorithms are evaluated.

关键词： NURBS surface Path Planning algorithms intelligent algorithms

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Machine Learning algorithms in Forecasting of Photovoltaic Power Generation 2

Machine Learning Algorithms in Forecasting of Photovoltaic P...

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2nd International Conference on Smart Energy Systems and Technologies (SEST)

作者： Su, Di Batzelis, Efstratios Pal, Bikash Imperial Coll London Elect & Elect Engn London England

ISBN: (纸本)9781728111568

Due to the intrinsic intermittency and stochastic nature of solar power, accurate forecasting of the photovoltaic (PV) generation is crucial for the operation and planning of PV-intensive power systems. Several PV forecasting methods based on machine learning algorithms have recently emerged, but a complete assessment of their performance on a common framework is still missing from the literature. In this paper, a comprehensive comparative analysis is performed, evaluating ten recent neural networks and intelligent algorithms of the literature in short-term PV forecasting. All methods are properly fine-tuned and assessed on a one-year dataset of a 406 MWp PV plant in the UK. Furthermore, a new hybrid prediction strategy is proposed and evaluated, derived as an aggregation of the most well-performing forecasting models. Simulation results in MATLAB show that the season of the year affects the accuracy of all methods, the proposed hybrid one performing most favorably overall.

关键词： Forecasting intelligent algorithms machine learning neural networks photovoltaic

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An environment-based network planning tool

An environment-based network planning tool

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12th IEEE International Symposium on Electron Devices for Microwave and Optoelectronic Applications

作者： Kurien, AM Van Wyk, BJ Snyman, LW Tshwane Univ Technol Dept Elect Engn ZA-0001 Pretoria South Africa

ISBN: (纸本)0780385748

Telecommunication networks across Africa have witnessed the widespread use of mobile technologies to meet the demands of access to basic telecommunication services. With the rapid growth of these networks, greater demands are being placed on the development of wireless networks in terms of efficiency and cost-effectiveness. This paper focuses on work currently being done in the development of a cellular network planning tool that takes into consideration various 'environment' related data to influence the traditional cellular network planning methodologies. Particular emphasis is placed on the utilization of so called 'intelligent' algorithms to make effective decisions in the choice optimum values for various parameters in network. Specific focus is made on the choice of base station placement and subscriber characteristic identification for capacity related planning.

关键词： radio planning intelligent algorithms

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Adaptive technology to support talented secondary school students with the educational IT infrastructure

Adaptive technology to support talented secondary school stu...

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IEEE Global Engineering Education Conference (EDUCON) - Emerging Trends and Challenges of Engineering Education

作者： Shukhman, Alexander E. Bolodurina, Irina P. Polezhaev, Petr N. Ushakov, Yury A. Legashev, Leonid V. Orenburg State Univ Dept Math & Informat Technol Orenburg Russia

ISBN: (纸本)9781538629574

This paper describes the project of an automated adaptive system for individual support of talented students with the educational IT infrastructure. A model of the process of self-learning and self-development of talented students in the educational IT infrastructure is developed on the basis of a multilevel competence system using Petri nets. To design optimal student's individual learning paths algorithms of the ant colony have been used. Methods for calculating the relative values of the student's rating are proposed based on accounting their academic achievements in a specific subject area. A preliminary version of the Web portal has been developed to provide the storage of talented student's profiles with their achievements and ratings, information on courses and training competitions, ILP planning, user interaction, integration with external educational resources.

关键词： learning management systems individual learning paths competency estimation intelligent algorithms

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Meta-heuristic bus transportation algorithm

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Iran Journal of Computer Science 2019年第1期2卷 23-32页

作者： Bodaghi, Mohammad Samieefar, Koosha Amirkabir University of Technology Tehran Iran

Over recent decades, several experience-based mathematical models have been proposed. In addition to collective intelligence, in recent years some efforts have been made to apply human experience-based intelligence to open up a new world of possibilities to design new meta-heuristic algorithms for solving NP problems. In these algorithms instead of only relying on collective intelligence, each individual tries to search for optimal solution based on her or his own experience and others. In this paper, we use a social behavior of humans in transportations to reach their destination and we took experience-based human behavior and smartness of humans as an inspiration to propose our meta-heuristic algorithm and we name it bus transportation algorithm. As a simple example, we restrict our paper to solve a well-known problem integer programming which is known as an NP-Complete problem. Compared to other algorithms, the results in these papers show that our algorithm outperforms PSO (particle swarm optimization), GA (genetic algorithm) and SA (simulated annealing) in terms of efficiency and convergence. © Springer Nature Switzerland AG 2018.

关键词： Bus transportation algorithm Empiricism Human intelligence intelligent algorithms Meta-heuristic algorithm

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Information Extraction System for Invoices and Receipts 1

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19th International Conference on Advanced intelligent Computing Technology and Applications (ICIC)

作者： Tan, QiuXing Michelle Cao, Qi Seow, Chee Kiat Yau, Peter Chunyu Univ Glasgow Comp Sci Singapore Inst Technol Singapore Singapore Univ Glasgow Sch Comp Sci Glasgow Lanark Scotland

ISBN: (数字)9789819947522

ISBN: (纸本)9789819947515;9789819947522

Rapid growth in the digitization of documents, such as paper-based invoices or receipts, has alleviated the demand for methods to process information accurately and efficiently. However, it has become impractical for humans to extract the data manually, as it is labor-intensive and time-consuming. Digital documents contain various components such as tables, key-value pairs and figures. Existing optical character recognition (OCR) methods can recognize texts, but it is challenging to extract the key-value pairs in unformatted digital invoices or receipts. Hence, developing an information extraction system with intelligent algorithms would be beneficial, as it can increase the workflow efficiency for knowledge discovery and data recognition. In this paper, a pipeline of the information extraction system is proposed with intelligent computing and deep learning approaches for classifying key-value pairs first, followed by linking the key-value pairs. Two key-value pairing rules are developed in the proposed pipeline. Various experiments with intelligent algorithms are conducted to evaluate the performance of the pipeline of information extraction system.

关键词： Information Extraction Key-Value Pairs Knowledge Discovery Documents Digitization intelligent algorithms

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Ethical Challenges and Governance of Smart algorithms Empowering Financial Technology 20th

Ethical Challenges and Governance of Smart Algorithms Empowe...

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20th International Conference on intelligent Computing (ICIC)

作者： Yan, Songlian Pan, Min Yu, Jiahui South China Normal Univ Guangzhou 528225 Peoples R China Henan Univ Finance & Law Zhengzhou 450046 Peoples R China

ISBN: (纸本)9789819756742;9789819756759

The application of intelligent algorithms in the financial field has significantly improved the efficiency and accuracy of financial services, but it also hides potential algorithmic ethical risks. This article first explains the application of intelligent algorithms in financial technology, and conducts an in-depth analysis of the ethical issues of intelligent algorithms in the financial field. Secondly, it defines the possible data privacy and security, algorithm discrimination, algorithm distortion, algorithm black box, and large model risks of intelligent algorithms. As well as specific ethical phenomena such as the issue of responsibility attribution, the causes of their occurrence are analyzed. Acknowledging that such dilemmas may pervade the entire life cycle from product development to application, this article elaborates on the possible social impacts and how to carry out the strategies for prevention or governance at various levels-technical, organizational, legal, and professional ethics. Finally, it was emphasized that while pursuing technological innovation and commercial benefits in the financial field, ethical considerations must be balanced, and an outlook was put forward on the development trend of intelligent algorithms in the future financial technology field.

关键词： intelligent algorithms Financial technology Algorithm ethics Ethical governance

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Impact of Extended-Life Noise and Temperature Measurements on Littoral ASW

Impact of Extended-Life Noise and Temperature Measurements o...

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Washington State Conference and Trade Center (WSCTC)

作者： DelBalzo, Donald R. Leclere, James H. Klicka, Joseph QinetiQ N Amer Technol Solut Grp 40201 Hwy 190 E Slidell LA 70461 USA Naval Air Syst Command PMA 264 Patuxent River MD 20670 USA

ISBN: (纸本)9781424443338

The U. S. Naval Air Systems Command is considering extended-life environmental sonobuoy concepts to better characterize littoral environments. Some conceptual designs contain thermistors to measure ocean temperatures and hydrophones to measure ambient noise. In this work, measured temperature profiles and predictions of ambient noise using ship densities in the Sea of Japan are used to simulate a) data collected with 3 "single-shot" fixed sonobuoys, b) data collected with 3 extended-life sonobuoys drifting over a 12-days, and c) "ground-truth" or actual conditions. Those environmental simulations are used to predict acoustic conditions;i.e., transmission loss, detection range, and detection probability at 100 Hz for an anti-submarine warfare application. The simulated environmental fields and predicted acoustic results for fixed and drifting sensors are compared to our best estimate of actual conditions. Results show that 3 drifting buoys yield significantly better representations of the actual temperatures, ambient noise, and derived acoustic fields than 3 discrete measurements. intelligent algorithms are used to locate tactical sonobuoys in the three environments. The calculated detection probabilities from the drifting buoy environment are 20% more accurate than those from the discretely measured environment.

关键词： Sea of Japan U.S. Naval Air Systems Command acoustic conditions acoustic fields ambient noise antisubmarine warfare application detection probability detection range extended-life noise extended-life sonobuoy drifting hydrophones hydrophones intelligent algorithms littoral ASW noise ocean temperature ocean temperatures oceanographic regions oceanographic techniques ship densities single-shot fixed sonobuoys temperature profiles thermistors thermistors transmission loss

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