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IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS)

作者： Chenglin Mou Kaiqi Wu Pengcheng Du Kaibo Yang Department of Engineering Mechanics School of Civil Engineering and Architecture Henan University of Science and Technology Luoyang China Department of Computer Science and Technology School of Information Engineering Henan University of Science and Technology Luoyang China Department of Automation School of Information Engineering Henan University of Science and Technology Luoyang China Department of Civil Engineering School of International Education Henan University of Science and Technology Luoyang China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

Tower solar thermal power generation is a new type of low-carbon and environmentally friendly clean energy technology. In this paper, a single-objective optimization model is established with the maximum annual average thermal output per unit mirror area of the heliostat field as the objective function. By optimizing the heliostat width, heliostat height and heliostat coordinate, the annual average output thermal power can be maximized while meeting the rated power. The heliostat field is distributed in a circular shape. As the seasons change, the light intensity received by the heliostat field is uneven, so the optical efficiency of the heliostats is also different. We simplify the heliostat field into S area (area with higher optical efficiency) and W area (area with lower optical efficiency) based on the optical efficiency distribution of heliostats. At different locations, According to the heliostat width, heliostat height and heliostat coordinate generated by random functions, substituting these parameters into the efficiency model in this paper, and the random search algorithm is used to traverse the maximum annual output thermal power and the corresponding heliostat parameters. In the shadow occlusion loss model, we have grid to set up the heliostat and use the coordinate conversion to solve the shadow occlusion loss efficiency.

关键词： Integrated optics Green energy Shape Optimization models Computational modeling Poles and towers Linear programming Mirrors Power generation

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Improving the Performance of Job Backfilling Based on Job's Weight and Back Propagation Neural Network

Improving the Performance of Job Backfilling Based on Job's ...

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Computational Intelligence Approaches and Applications (ICCIAA), International Conference on

作者： Hazem Alnajjar Nadia Al-Rousan Syed Sahal Nazli Alhady Syed Hassan Junita Mohamad-Saleh Department of Computer Science College of Information Technology University of Petra Amman Jordan Department of computer engineering College of Engineering AlBalqa Applied University Salt Jordan Department of Computer Engineering Faculty of Electrical Engineering and Information Systems German Jordanian University Amman Jordan Colleage of Engineering and Architecture School of Electrical & Electronic Engineering Engineering Branch Campus Universiti Sains Malaysia Malaysia

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

Nowadays, the grid computing environment faces many difficulties executing new jobs, especially jobs requiring large resource requirements and long execution times. This motivates researchers and scholars to find cheap and fast methods to improve the efficiency of grid environments. One of the cheap and fast methods is to implement job scheduling algorithms based on cheap and fast techniques. This paper proposes a new job ranking backfilling algorithm based on the job's weight and back propagation neural network. To define the weight of the job, first, the proposed model will use a clustering algorithm to cluster the job's dataset into groups, and then the groups will be ranked using an experimental ranking equation. A discrete event simulator is used to validate the proposed algorithm's capability and robustness. The average results revealed that the new algorithm outperforms previous algorithms. The improvement of the studied metrics is between 1.19 and 6.30, respectively. The results proved that the proposed model is efficient and can be used with low overhead in a real environment.

关键词： Backpropagation Measurement Scheduling algorithms Computational modeling Neural networks Clustering algorithms Grid computing Mathematical models Robustness Faces

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Spline Global MPPT with PID Controller Based on Levy Invasive Weed Technique for Renewable Energy Resources of Smart Homes

Spline Global MPPT with PID Controller Based on Levy Invasiv...

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IEEE International Conference on Power and Power and Renewable Energy (ICPRE)

作者： Aziza I. Hussein Mady Mohammad Passent Elkafrawy Rabab Hamed M. Aly College of Engineering Energy and Technology Research Center Effat University Jeddah Saudi Arabia College of Architecture Effat University Jeddah Saudi Arabia The Higher Institute for Management and Information Technology Minya Egypt Computer Science Department Faculty of Computer Science Nahda University Beni Suef Egypt

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

Renewable energy systems, particularly photovoltaic (PV) systems, have been played important role in the reducing carbon emissions. A primary concern in the field of photovoltaics (PV) based on the design of the maximum power point tracking (MPPT) is the capacity to accurately monitor power across many parameters in addition to ascertain the power production of solar cells or wind turbines and adjust the load to maximise power efficiency under varying weather conditions. On another hands, the hybrid smart system uses a wind catcher to reduce the amount of energy consumed by buildings from the grid, which is a historically significant architectural component for cross ventilation and passive cooling. This paper presents an updating of model that proposes improvements to the regulation of Spline MPPT with tuning PID controller by using Levy Invasive Weed optimization (LIWO)technique. A rapid, accurate, and straightforward approach for determining the (MPPT) of PV systems under consistent irradiation and partial shade, as well as wind turbines, is presented using the Spline- MPPT technique. The model of this paper employs LIWO in conjunction with a PID controller to improve the selection of PID gains. Moreover, is applied to generate the optimal values of duty cycle of the model. The comprehensive system design depicted has been simulated using MATLAB Simulink to verify the functionality of the system. The model has attained an accuracy of 93%. The outcomes of this model contribute greatly to our understanding of the suitability and efficacy of both AI and traditional MPPT controllers. This modeling will be beneficial to the renewable energy industry.

关键词： Maximum power point trackers Photovoltaic systems Renewable energy sources Accuracy Software packages Mathematical models Wind turbines Splines (mathematics) Optimization Tuning

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ERS: a novel comprehensive endoscopy image dataset for machine learning, compliant with the MST 3.0 specification

arXiv

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arXiv 2022年

作者： Cychnerski, Jan Dziubich, Tomasz Brzeski, Adam Department of Computer Architecture Gdańsk University of Technology Narutowicza 11/12 Gdańsk Poland

The article presents a new multi-label comprehensive image dataset from flexible endoscopy, colonoscopy and capsule endoscopy, named ERS. The collection has been labeled according to the full medical specification of'Minimum Standard Terminology 3.0' (MST 3.0), describing all possible findings in the gastrointestinal tract (104 possible labels), extended with an additional 19 labels useful in common machine learning applications. The dataset contains around 6000 precisely and 115,000 approximately labeled frames from endoscopy videos, 3600 precise and 22,600 approximate segmentation masks, and 1.23 million unlabeled frames from flexible and capsule endoscopy videos. The labeled data cover almost entirely the MST 3.0 standard. The data came from 1520 videos of 1135 patients. Additionally, this paper proposes and describes four exemplary experiments in gastrointestinal image classification task performed using the created dataset. The obtained results indicate the high usefulness and flexibility of the dataset in training and testing machine learning algorithms in the field of endoscopic data analysis. © 2022, CC BY-SA.

关键词： Image recognition

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Joint Prediction of SOH and RUL for Lithium Batteries Considering Capacity Self Recovery and Model Drift

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IEEE Internet of Things Journal 2025年

作者： Jia, Zhen Li, Zhifei Wang, Zhengdong Liu, Zhenbao Vong, Chi-Man Xi'an University of Architecture and Technology School of Mechanical and Electrical Engineering Xi'an710055 China Northwestern Polytechnical University School of Civil Aviation Xi'an710072 China University of Macau Department of Computer and Informa tion Science Macau999078 China

Accurate monitoring of the state of health (SOH) and remaining useful life (RUL) of lithium batteries is a key technology to realize their stable and economic operation. The current data-driven methods have problems such as local prediction errors caused by capacity self-recovery effect, model drift phenomenon, and inaccurate trend prediction caused by complex degradation process. In this paper, we propose a joint SOH and RUL forecasting based on the fusion of Kolmogorov-Arnold Network (KAN), Deep Bidirectional Long Short-Term Memory Network (DBLSTM) and adaptive mechanism method (KAN-HDBLSTM-AM). The method innovatively introduces an adaptive mechanism that considers the capacity degradation trend for different prediction steps, suppresses the accumulation of errors in the model prediction process, and further improves the prediction accuracy by combining the nonlinear approximation capability of KAN and the mastery of data temporal characteristics of DBLSTM. Experimental validation shows that the proposed method can effectively overcome the prediction errors caused by capacity self-recovery and model drift, and can retain sufficient accuracy under long prediction steps, with the prediction trend being more in line with the actual change trend and the prediction error being smaller compared with other methods. © 2014 IEEE.

关键词： Prediction models

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Brain Cortical Surface Can Predict Fiber Trajectories

Brain Cortical Surface Can Predict Fiber Trajectories

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IEEE International Symposium on Biomedical Imaging

作者： Tianle Han Yifan Lv Mengshen He Yiheng Liu Tianming Liu Bao Ge School of Physics & Information Technology Shaanxi Normal University Xi'an China Department of Computer Science and Bioimaging Research Center Cortical Architecture Imaging and Discovery Lab The University of Georgia GA USA

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Gray matter and white matter are fundamental constituents of the brain, and exploring the relationship between them is for gaining insights into the intricate architecture of the brain. This study utilizes information extracted from the gray matter surface of the brain to predict the trajectories of white matter fibers. Specifically, it predicts the coordinates of fiber trajectories by utilizing both fiber endpoints and reference points on the cortical surface. Both qualitative analysis and extensive quantitative experiments confirm that information derived from the brain's cortical surface can be employed to predict fiber trajectories. Furthermore, this conclusion remains robust across diverse fiber tracking and surface reconstruction techniques. The study introduces a novel perspective, elucidating the fundamental principles of fiber connectivity and the intricate relationship between gray matter and white matter.

关键词： Surface reconstruction Brain Pathology Nerve fibers Magnetic resonance imaging Grey matter Streaming media

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Improving Genetic Algorithms Performance via Deterministic Population Shrinkage

arXiv

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arXiv 2024年

作者： Laredo, Juan Luis Jiménez Fernandes, Carlos Merelo, Juan Julián Gagné, Christian Department of Architecture and Computer Technology University of Granada Spain LASEEB-ISR/IST University of Lisbon Portugal Laboratoire de vision et systèmes numériques Laval University Canada

Despite the intuition that the same population size is not needed throughout the run of an Evolutionary Algorithm (EA), most EAs use a fixed population size. This paper presents an empirical study on the possible benefits of a Simple Variable Population Sizing (SVPS) scheme on the performance of Genetic Algorithms (GAs). It consists in decreasing the population for a GA run following a predetermined schedule, configured by a speed and a severity parameter. The method uses as initial population size an estimation of the minimum size needed to supply enough building blocks, using a fixed-size selectorecombinative GA converging within some confidence interval toward good solutions for a particular problem. Following this methodology, a scalability analysis is conducted on deceptive, quasi-deceptive, and non-deceptive trap functions in order to assess whether SVPS-GA improves performances compared to a fixed-size GA under different problem instances and difficulty levels. Results show several combinations of speed-severity where SVPS-GA preserves the solution quality while improving performances, by reducing the number of evaluations needed for success. © 2024, CC BY.

关键词： Genetic algorithms

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Reconstruction of the Mosul Old City by Procedural Modelling

SSRN

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SSRN 2024年

作者： Hussein, Khalid Ahmed Ismaeel, Emad Hani Ihsan, Rasheed Rebar Sadeeq, Haval Tariq Architecture Engineering Department College of Engineering Nawroz University KRD Duhok Iraq Dept. of Architecture Coll. of Engineering University of Mosul Iraq Computer and Communication Department College of Engineering Nawroz University KRD Duhok Iraq Information Technology Department Technical College of Duhok Duhok Polytechnic University KRD Region Iraq

The old city of Mosul possesses a rich built heritage, featuring distinct architectural styles evolved, incorporating indigenous knowledge and expertise to address functional, climatic, economic, and construction requirements. Tragically, during the military operations in 2016-2017, Mosul Old City experienced extensive devastation, resulting in the loss of numerous landmarks and the irreplaceable built heritage of this city. However, digitization has emerged as a potent heritage preservation and restoration tool. It serves as a vital initial step in reviving deteriorated heritage by providing invaluable information to specialists. In light of this, the present study aims to regenerate the urban facades of Mosul's old city automatically, ensuring they retain their original characteristics. This objective will be accomplished by utilizing procedural modelling techniques and algorithms incorporating specific characteristics as constraints within the regeneration process. The research makes a notable contribution to digital architectural design by employing Shape Grammar analysis to derive rules. Subsequently, these rules are implemented through Python to facilitate the automatic generation of 750 heritage facade designs. Ultimately, the study demonstrates the feasibility of using procedural modelling to recreate the decimated urban fabric, ensuring the restored structures exhibit the same formal and structural characteristics as their predecessors. © 2024, The Authors. All rights reserved.

关键词： Python

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A survey and recent advances in black widow optimization: variants and applications

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Neural Computing and Applications 2024年 1-21页

作者： Shehab, Mohammad Shambour, Mohd Khaled Yousef Abu Hashem, Muhannad A. Al Hamad, Husam Ahmad Shannaq, Fatima Mizher, Manar Jaradat, Ghaith Sh. Daoud, Mohammad Abualigah, Laith College of Computer Sciences and Informatics Amman Arab University Amman11953 Jordan The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research Umm Al-Qura University Makkah Saudi Arabia Department of Geomatics Architecture and Planning Faculty King Abdulaziz University Jeddah Saudi Arabia College of Engineering Al Ain University Abu Dhabi United Arab Emirates Research Center University of Tabuk Tabuk71491 Saudi Arabia Computer Science Department Al al-Bayt University Mafraq25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia Applied science research center Applied science private university Amman11931 Jordan College of Engineering Yuan Ze University Taoyuan32003 Taiwan

Artificial Intelligence techniques, such as optimization algorithms, have become essential for success in many fields. Therefore, most researchers, especially in computer and engineering sciences, focused their efforts and abilities on adapting the optimization algorithms for solving various problems. This review introduces one of the recent nature-inspired optimization algorithms, called black widow optimization (BWO). This review highlights the main procedures of BWO, its strengths and weaknesses, the growth of BWO, the variants of BWO (i.e., binary, modification, and hybridization), and the efficiency of BWO in different fields and applications (i.e., feature selection, medical, image processing, engineering, IoT, power and energy, and networks). As a result, the review seeks to assist researchers who are interested in using the BWO to address their challenges. For instance, it could help manage large pilgrim crowds, enabling smoother ritual performances and overcoming potential difficulties they encounter. Also, it suggests new possible ways of enhancing the efficiency of the basic BWO. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Optimization

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Effect of Artificial Roughness on Heat Transfer and Friction Factor in a Solar Air Heater: A Review 2nd

Effect of Artificial Roughness on Heat Transfer and Friction...

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2nd International Conference on Advances in Materials and Manufacturing technology, ICAMMT 2022

作者： Yadav, Anil Singh Alam, Tabish Saxena, Rajiv Yadav, Raj Kumar Kumar, Rajan Sharma, Abhishek Agrawal, Yogesh Viswanath Allamraju, K. Vyas, Monika Singh, Manmohan Chakroborty, Subhendu Mechanical Engineering Department IES College of Technology MP Bhopal462044 India Architecture Planning and Energy Efficiency CSIR-Central Building Research Institute Uttarakhand Roorkee247667 India Infinity Management and Engineering College MP Sagar470001 India Mechanical Engineering Department Adina Institute of Science and Technology MP Sagar470002 India Department of Mechanical Engineering BIT Sindri Jharkhand Dhanbad828123 India Mechanical Engineering Department Sagar Institute of Research and Technology MP Bhopal462041 India Mechanical Engineering Department Institute of Aeronautical Engineering Telangana Hyderabad500043 India Civil Engineering Department IES College of Technology MP Bhopal462044 India Computer Science and Engineering Department IES College of Technology MP Bhopal462044 India Department of Basic Sciences IITM IES University MP Bhopal462044 India

ISBN: (纸本)9789819929207

In order to convert solar energy into thermal energy, solar air heater (SAH) is commonly used. These are used to convert the solar radiation into heat of working fluid. The effect of various geometric constraints on the friction characteristics and heat transfer (HT) of a SAH has been studied. The paper aims to introduce the various parameters that are involved in the analysis of HT enhancement of SAH. There are various techniques that are involved in the analysis of HT enhancement of SAH. One of these is the use of a passive method, which involves the use of turbulators, ribs or fins on the surface. SAHs that are roughened can improve their HT properties compared to their plain counterparts. This is because the various surface patterns and shapes used in their design can help improve their performance. There have been many different sorts of studies conducted on the many facets of these HT augmentation approaches. Studies showed that combining the roughening process with a rough absorber plate can improve the performance of SAH duct. The goal of this study is to identify the most appropriate roughness component for solar air duct that can meet the different operating conditions. The findings of this study can be used to design and construct enhanced SAH duct system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Flow of fluids

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