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Forecasting and managing urban futures: machine learning models and optimization of urban expansion

Asian Journal of Civil Engineering 2024年第6期25卷 4673-4682页

作者： Abid, Mohammed Talib Aljarrah, Njood Shraa, Tamer Alghananim, Haneen Marouf Department of Architecture College of Engineering Al-Nahrain University Baghdah Iraq Computer Sciences Faculty of Information Technology and Computer Sciences Ajloun National University Ajloun Jordan Faculty of Science and Information Technology Cyber Security Irbid National University Irbid Jordan Faculty of Engineering Architecture Department Ain Shams University Cairo Egypt

This paper presents a novel method for predicting and controlling urban growth by combining convolutional neural networks (CNN) with Spider Monkey Optimization (SMO) to efficiently use their combined capabilities. This strategy utilizes sophisticated machine learning algorithms to forecast urban development patterns, while optimization technologies enhance these forecasts by including sustainable urban design ideas. Integration plays a crucial role in tackling the difficulties presented by fast urbanization, including issues related to land use, resource administration, and environmental sustainability in the fields of civil and architectural engineering. The study employs large datasets to assess the efficacy of CNN models in detecting urban expansion patterns and enhances these models with optimization scenarios encompassing land use, traffic flow, electricity efficiency, water resources, and waste management, all with the goal of enhancing urban sustainability. The findings demonstrate a significant improvement in the precision of predictions and the ability to maintain positive results, highlighting the crucial role of integrating machine learning and optimization in urban planning methodologies. This method not only provides urban planners and politicians with strong and effective tools for making decisions but also creates opportunities for implementing creative and sustainable solutions for urban growth. The results provide a substantial contribution to the existing urban planning literature by demonstrating the actual use of these technologies in regulating urban expansion. This will stimulate more study in this rapidly evolving subject. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Convolutional neural networks Machine learning Optimization techniques Spider monkey optimization Sustainable urban planning Urban expansion

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An Intelligent Optimization Method of Reinforcing Bar Cutting for Construction Site

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computer Modeling in Engineering & Sciences 2023年第1期134卷 637-655页

作者： Zhaoxi Ma Qin Zhao Tianyou Cang Zongjian Li Yiyun Zhu Xinhong Hei Department of Civil Engineering and Architecture Xi’an University of TechnologyXi’an710048China State Key Laboratory of Rail Transit Engineering Informatization(FSDI) Xi’an710043China Department of Computer Science and Engineering Xi’an University of TechnologyXi’an710048China

To meet the requirements of specifications,intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable *** one of the most important building materials in construction engineering,reinforcing bars(rebar)account for more than 30%of the cost in civil engineering.A significant amount of cutting waste is generated during the construction *** cutting waste increases construction costs and generates a considerable amount of CO_(2)*** study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable *** the proposed algorithm,the integer linear programming algorithm was applied to solve the *** was combined with the statistical method,a greedy strategy was introduced,and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data *** proposed algorithm was verified through a case study;the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124%compared with that of traditional distributed processing of steel bars,reducing CO_(2)emissions and saving construction *** the scale of a project increases,the calculation quality of the optimization algorithmfor steel bar blanking proposed also increases,while maintaining high calculation *** the results of this study are applied in practice,they can be used as a sustainable foundation for building informatization and intelligent development.

关键词： Building construction rebar work cutting stock problem optimization algorithm integer linear programming

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Collection and Storage of Technological Data in Multi-Channel CNC Processing Using a Non-Relational Database and Node-RED

Collection and Storage of Technological Data in Multi-Channe...

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2023 International Russian Automation Conference, RusAutoCon 2023

作者： Martinov, Georgi Polyakov, Kirill Moscow State University of Technology "STANKIN" Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9798350345551

This article contemplates the problem of collecting and storing technological data during multichannel and multi - coordinate machining on CNC machines obtained using the OPC UA protocol and applying Node-RED open-source instrumentation. A structural model of obtaining, visualizing and storing technological data in multichannel and multi - coordinate machining is proposed in this research. The necessary nodes for Collection and storage of technological data in multi-channel CNC processing are implemented and configured. The researchers illustrated practical aspects of building a system for collecting and storing technological data in multichannel machining using the OPC UA protocol and applying Node-RED open-source tools and a non-relational MongoDB database. © 2023 IEEE.

关键词： Digital storage

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Development and Use of OPC UA Tools for Data Collection and Monitoring of Technological Equipment

Development and Use of OPC UA Tools for Data Collection and ...

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2023 International Russian Smart Industry Conference, SmartIndustryCon 2023

作者： Martinov, Georgi Al Khoury, Akram Issa, Ahed Moscow State University of Technology STANKIN Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9781665464291

The aim of this research is to develop a specialized system for collecting and storing CNC machines data considering the possibilities of innovative technologies of OPC UA protocol, in this work an OPC UA information model was proposed and realized in OPC UA server which reflects the logical structure of a CNC machine. This research will present a collecting data method from the digital shadow of CNC system where a complete set of parameters hierarchically structured and transmit the whole set of these parameters through the OPC UA server to production data collection cloud for performing subsequent analyzing, forecasting the state of technological equipment and performing simulation procedures. © 2023 IEEE.

关键词： Data acquisition

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An Approach to the Production of Prototype Printed Circuit Boards on Bench-Type Machine with the CNC System

An Approach to the Production of Prototype Printed Circuit B...

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2023 International Russian Smart Industry Conference, SmartIndustryCon 2023

作者： Martinov, Georgi Martemianova, Natalia Moscow State University of Technology "STANKIN" Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9781665464291

The paper considers the problems of manufacturing prototypes of printed circuit boards on bench-Type milling machines that require the prompt production of a small batch and correction, if it's necessary. We used modern tools from third-party manufacturers for the preparation of production and processing of single-and double-layer printed circuit boards on bench-Type CNC machines. A technique is proposed that formalizes the process of preparing and verifying part programs and manufacturing printed circuit boards. The methodology was tested and an example of manufacturing a prototype of a printed circuit board for a voltage regulator on a machine with an "AxiOMA Control"CNC system was illustrated. © 2023 IEEE.

关键词： Printed circuit boards

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The Practice of Using a SoftPLC to Control the Electromechanical Units of a Training Turning Machine

The Practice of Using a SoftPLC to Control the Electromechan...

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2023 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Martinov, Georgi Nikishechkin, Petr A. Moscow State University of Technology Stankin Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9781665475952

The process of developing a PLC program for controlling the electromechanical units of modern machine tools with computer numerical control (CNC) has been formalized. The architecture of a two-computer CNC system with an integrated SoftPLC is given and the specifics of using the touch operator panel and virtual machine panel are considered. A set of libraries developed in the FBD (Functional Block Diagram) language for controlling the electrical automation units of a turning machine is proposed. An example of controlling the electric automation of a training lathe via the high-speed EtherCAT field bus using relatively inexpensive third-party solutions for servo drives and I/O modules that provide the required accuracy and speed is given. © 2023 IEEE.

关键词： Lathes

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The Specifics of Building a Cross-Platform OPC UA Server for a CNC System

The Specifics of Building a Cross-Platform OPC UA Server for...

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2023 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Martinov, Georgi Zakharov, Alexander Moscow State University of Technology Stankin Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9781665475952

There is a justified need for a cross-platform implementation of an OPC UA server for a CNC system. The available open-source libraries that implement the OPC UA stack have been analyzed, and a solution based on open62541 has been selected. An architectural model for the interaction between the OPC UA server and the CNC system core has been proposed. In addition to the traditional mechanism for obtaining current data values from the CNC system core, the OPC UA server implements a mechanism for working with historical data and a mechanism for controlling the CNC system by sending commands through a control channel via a callback method. Class diagrams illustrating the implementation of these mechanisms have been provided. An OPC UA client has been developed in C# programming language for testing the cross-platform OPC UA server of the CNC system. © 2023 IEEE.

关键词： Open source software

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The Mechanism for Synchronizing CNC System with External Devices by Using a Part Program

The Mechanism for Synchronizing CNC System with External Dev...

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2023 International Russian Automation Conference, RusAutoCon 2023

作者： Martinov, Georgi Salamatin, Evgeny Moscow State University of Technology "STANKIN" Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9798350345551

The problem of synchronizing parallel tasks in control systems at the level of the part program is reviewed. A general solution, based on a high-level part programming language extension, is proposed for synchronizing parallel tasks within one control system as well as tasks performed by several different control systems. A scheme for synchronizing the CNC with external autonomous devices through the Common PLC Memory, to which the part program, the PLC program and the inputs and outputs (I/Os) of electric automation have access, has been developed. A set of functions in a high-level part programming language, providing zeroing a certain number of bytes, writing bit, byte, long and float data types to the Common PLC Memory and reading them from it, has been implemented. As a part of practical research, a test stand on the basis of the AxiOMA Control CNC system, that controls actuators via the EtherCAT protocol, was assembled;master and slave part programs were implemented;tests, confirming the operability of the mechanism for synchronizing CNC system with external devices by using a part program, were carried out. © 2023 IEEE.

关键词： Control systems

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A Comparative Study on Deep Learning Models for Stock Price Prediction 5

A Comparative Study on Deep Learning Models for Stock Price ...

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5th Asia-Pacific Conference on Image Processing, Electronics and computers, IPEC 2024

作者： He, Zhexin Zhang, Huan Por, Lip Yee Chongqing College of Architecture and Technology Chongqing401331 China Chongqing Academy of Science and Technology Chongqing401123 China Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur50603 Malaysia

ISBN: (纸本)9781643685243

With the advancement of deep learning technology, researchers have begun employing deep neural network models such as LSTM, MLP, CNN, and GRU to tackle nonlinear prediction problems in stock markets. This study harnesses these deep learning models, including LSTM, MLP, CNN, and GRU, to investigate the nonlinear forecasting of stock market price indices. The experiment selects globally representative stock indices and, through analyzing short-term, mid-term, and long-term data, discovers that the GRU model demonstrates exceptional performance in both prediction accuracy and generalization capabilities. To further enhance precision, the research constructs a filtering ensemble decision-making system based on multiple GRU models. This strategy reduces the error by at least 0.3% in medium to long-term predictions, significantly outperforming a single standalone GRU model. Consequently, the GRU-filtered ensemble decision model has been empirically proven as an effective tool for predicting stock indices, not only broadening the methods available for stock market prediction but also deepening the understanding and application of the generalization abilities of deep learning models within financial markets. © 2024 The Authors.

关键词： Long short-term memory

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The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities:A comprehensive systematic review

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Environmental Science and Ecotechnology 2024年第4期20卷 79-104页

作者： Simon Elias Bibri Jeffrey Huang Senthil Kumar Jagatheesaperumal John Krogstie Swiss Federal Institute of Technology Lausanne(EPFL) Institute of Computer and Communication Sciences(IINFCOM)School of ArchitectureCivil and Environmental Engineering(ENAC)Media and Design Laboratory(LDM)1015LausanneSwitzerland Department of Electronics&Communication Engineering Mepco Schlenk Engineering CollegeSivakasi626005TamilnaduIndia Department of Computer Science Norwegian University of Science and Technology(NTNU)TrondheimNorway

The dynamic landscape of sustainable smart cities is witnessing a significant transformation due to the integration of emerging computational technologies and innovative *** advancements are reshaping data-driven planning strategies,practices,and approaches,thereby facilitating the achievement of environmental sustainability *** transformative wave signals a fundamental shift d marked by the synergistic operation of artificial intelligence(AI),artificial intelligence of things(AIoT),and urban digital twin(UDT)*** previous research has largely explored urban AI,urban AIoT,and UDT in isolation,a significant knowledge gap exists regarding their synergistic interplay,collaborative integration,and collective impact on data-driven environmental planning in the dynamic context of sustainable smart *** address this gap,this study conducts a comprehensive systematic review to uncover the intricate interactions among these interconnected technologies,models,and domains while elucidating the nuanced dynamics and untapped synergies in the complex ecosystem of sustainable smart *** to this study are four guiding research questions:*** theoretical and practical foundations underpin the convergence of AI,AIoT,UDT,data-driven planning,and environmental sustainability in sustainable smart cities,and how can these components be synthesized into a novel comprehensive framework?*** does integrating AI and AIoT reshape the landscape of datadriven planning to improve the environmental performance of sustainable smart cities?*** can AI and AIoT augment the capabilities of UDT to enhance data-driven environmental planning processes in sustainable smart cities?*** challenges and barriers arise in integrating and implementing AI,AIoT,and UDT in data-driven environmental urban planning,and what strategies can be devised to surmount or mitigate them?Methodologically,this study involves a rigorous analysis and synthesis of studies publis

关键词： Sustainable smart cities Artificial intelligence Artificial intelligence of things Urban digital twin Data-driven urban planning Environmental planning Environmental sustainability

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