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Evaluating machine learning models and feature selection for reference evapotranspiration estimation in semi-arid regions: a case study in Doukkala, Morocco

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Theoretical and Applied Climatology 2025年第6期156卷 1-24页

作者： Belarbi, Zaid EL Younoussi, Yacine Information System and Software Engineering Laboratory Abdelmalek Essaadi University Tetouan Morocco

Accurate estimation of reference evapotranspiration (ETo) is crucial for effective water resource management and irrigation planning, particularly in regions with significant agricultural activity, such as Doukkala, Morocco. This study explores the potential of machine learning (ML) models to estimate daily ETo using 18 years of climatic data collected from two meteorological stations in the region. The dataset includes key meteorological variables—temperature, humidity, solar radiation, wind speed, and rainfall—with ETo calculated using the FAO-56 Penman-Monteith (PM) equation as the reference. A range of ML models, including Artificial Neural Networks (ANN), Support Vector Regression (SVR), XGBoost, Random Forest (RF), k-Nearest Neighbors (KNN), Decision Trees (DT), and Multiple Linear Regression (MLR), were trained and compared. Additionally, deep learning architectures such as Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN) were evaluated for their ability to capture temporal dependencies within the data. Among the tested models, ANN demonstrated the highest performance, achieving an R² of 0.9868 and an MSE of 0.0440, followed closely by SVR and XGBoost, both of which also exhibited high predictive accuracy. In contrast, simpler models like MLR and DT showed comparatively lower performance, underscoring the advantages of more advanced ML techniques for ETo estimation. While LSTM displayed moderate success, CNN underperformed relative to other models. The inclusion of data from two stations enabled the evaluation of model generalizability across distinct locations within the region. However, this study has some limitations. While cross-site validation improves generalizability, the findings are based on two stations within the same semi-arid region, which may not fully represent ETo dynamics in more diverse climatic conditions. Additionally, while ML models demonstrated strong predictive capabilities, further improvements could be achieved b

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Ant Colony Optimization with Genetic Algorithm for Solving the Job Shop Scheduling 1st

Ant Colony Optimization with Genetic Algorithm for Solving t...

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1st International Conference on Electrical systems and Smart Technologies, ICESST 2024

作者： Kriouich, Mohamed Sarir, Hicham Information System and Software Engineering ENSA Tetouan Abdelmalek Esaadi University Tetouan Morocco

ISBN: (纸本)9783031867040

In dynamic manufacturing contexts, the Job-Shop Scheduling Problem (JSP) presents considerable hurdles, particularly in light of uncertainties such as machine breakdowns and job reworks. In this article, multiple scheduling algorithms are evaluated in various scenarios, with a special emphasis on lowering makespan, or overall completion time. Advanced algorithms like Genetic Algorithm (GA) and Deep Reinforcement Learning (DRL) are contrasted with heuristic techniques like Shortest Processing Time (SPT), Longest Processing Time (LPT), and First-In-First-Out (FIFO). The research emphasizes the advantages of the hybrid Ant Colony Optimization with Genetic Algorithm (ACO_GA) solution that has been suggested. Although GA and DRL produce outcomes that are competitive, ACO_GA regularly performs better than them and, in most cases, comes quite close to the optimal solution. Even in the face of difficult, real-world problems, our hybrid approach yields more reliable and nearly optimal scheduling solutions by fusing the exploration potential of ACO with the refinement power of GA. The results show how adaptable and successful ACO_GA is, which makes it the best option for solving JSP in dynamic contexts. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Ant colony optimization

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Development of a Methodology for Assessing the Performance of information Exchanges with Sources of Code Messages

Development of a Methodology for Assessing the Performance o...

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2024 International Russian Automation Conference, RusAutoCon 2024

作者： Bain, A.M. Portnov, E.M. Sin, Si Thu Thant Institute of System and Software Engineering and Information Technologies National Research University Miet Moscow Zelenograd Russia

In this paper, we developed a method to calculate the time parameters for interfacing with code message sources (CMS). This method enables the evaluation of how the collection and delivery time of information from CMS to the automated control system of the energy supply control system dispatcher varies based on the communication channel speed. Additionally, it accounts for the different numbers of CMS connected to a single control point. by analyzing these factors, the method provides insights into optimizing information transmission efficiency and ensures reliable data flow from CMS to the dispatcher's automated control system, thereby enhancing the overall performance and responsiveness of the energy supply control system. This development is crucial for improving the management and coordination within energy supply systems, ensuring timely and accurate information delivery, and ultimately contributing to more effective energy resource management. © 2024 IEEE.

关键词： Resource allocation

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Processing of Nonlinear Heterogeneous Data in information and Control systems

Processing of Nonlinear Heterogeneous Data in Information an...

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2024 International Russian Smart Industry Conference, SmartIndustryCon 2024

作者： Shevnina, Yu.S. Tsarapkin, S.F. Sin, Si Thu Thant Institute of System and Software Engineering and Information Technologies National Research University Miet Moscow Zelenograd Russia

ISBN: (纸本)9798350395044

The article presents a method for cluster analysis of heterogeneous data using the provisions of fuzzy logic. Heterogeneous are data of various formats and collected from various sources. In addition, such data is usually incomplete and inaccurate, which makes it difficult to process and cluster them. The article presents mathematical models for representing a candidate for a vacant position, which is characterized by heterogeneous data. The apparatus of algebraic systems was used to develop mathematical models. A method for determining the membership function of fuzzy sets using a probabilistic approach, as the most effective when working with heterogeneous data, is described in detail. An example of the formation of a base of logical rules for the formation and selection of classification features in a set of heterogeneous data of the personnel reserve of a manufacturing enterprise is given. The selected classification features allow for further accurate and efficient verification and evaluation of information about candidates for a vacant position. In addition, the proposed method of cluster analysis of heterogeneous data can be applied in various subject areas that involve the use of incomplete and inaccurate data, for example, socio-economic, technical, biological systems. © 2024 IEEE.

关键词： Membership functions

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Modeling of a Digital Twin of an Automated Production Process

Modeling of a Digital Twin of an Automated Production Proces...

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2024 International Russian Smart Industry Conference, SmartIndustryCon 2024

作者： Shevnina, Yu.S. Gagarina, L.G. Konyuhov, E.V. Institute of System and Software Engineering and Information Technologies National Research University Miet Moscow Zelenograd Russia

ISBN: (纸本)9798350395044

The article discusses the methodology for modeling a digital twin of an automated production process. The basis of the methodology is the method of intellectual analysis and information processing, which involves identifying patterns in the features, characteristics and parameters of the production process, forming classifiers for them according to various criteria in order to determine and predict the behavior of the process. The proposed digital twin modeling technique allows us to take into account hidden connections between the characteristics of the production process and their combinations, which increases the accuracy of forecasting changes in process behavior and, as a result, increases the efficiency of its management. As an example, the use of the proposed approaches for modeling a digital twin of automated assembly operations is considered. © 2024 IEEE.

关键词： Classification (of information)

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Development of a Method for Detecting Fruit Maturity Based on the Use of Neural Network Technologies

Development of a Method for Detecting Fruit Maturity Based o...

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2024 Conference of Young Researchers in Electrical and Electronic engineering, ElCon 2024

作者： Zaw, Hein Htet Win, Khant Zin Portnov, Evgeniy M. National Research University of Electronic Technology Zelenograd Institute of System and Software Engineering and Information Technologies Moscow Russia

ISBN: (纸本)9798350360646

The article substantiates the need to use neural network algorithms to search for mature crops and optimize harvesting equipment routes based on the data obtained. A technique for detecting fruit maturity based on the use of neural network technologies has been developed. The experiments have shown that the accuracy of the neural network algorithm developed in this dissertation work significantly exceeds the standard YOLOv4 neural networks. © 2024 IEEE.

关键词： image preprocessing maturity determination neural network algorithm

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Internet Banking Acceptance Towards Improving Sustainability: A systematic Literature Review 9

Internet Banking Acceptance Towards Improving Sustainability...

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9th International Conference on information Management, ICIM 2023

作者： Aziz, Khairi Azhar Abdullah, Salfarina Jabar, Marzanah A. Nor, Rozi Nor Haizan Jusoh, Yusmadi Yah Universiti Putra Malaysia Department of Software Engineering and Information System Selangor Serdang Malaysia

ISBN: (纸本)9798350336382

Internet banking is nowadays an important platform for taking care of financial matters. Researchers have introduced the acceptance of internet banking, which allows users to fulfil their obligations without visiting a counter. Nevertheless, the lack of sustainability of internet banking acceptance can systematically present the current research. The proposed study proposes a systematic literature review on internet banking acceptance to overcome this limitation. This systematic literature review (SLR) will help practitioners to draw on the existing literature and propose new solutions based on the existing internet banking adoption. The results of this paper can help future researchers from industry and academia by providing a guide for practitioners to identify approaches to successfully implement internet banking acceptance. © 2023 IEEE.

关键词： Sustainable development

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Static Analysis Techniques for Fixing software Defects in MPI-Based Parallel Programs

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Computers, Materials & Continua 2024年第5期79卷 3139-3173页

作者： Norah Abdullah Al-Johany Sanaa Abdullah Sharaf Fathy Elbouraey Eassa Reem Abdulaziz Alnanih Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Software Engineering and Distributed System Research Group King Abdulaziz UniversityJeddah21589Saudi Arabia

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed ***, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

关键词： High-performance computing parallel computing software engineering software defect message passing interface deadlock

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An Uncertainty Quantization-Based Method for Anti-UAV Detection in Infrared Images

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Computers, Materials & Continua 2025年第4期83卷 1439-1458页

作者： Can Wu Wenyi Tang Yunbo Rao Yinjie Chen Hui Ding Shuzhen Zhu Yuanyuan Wang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu610054China State Key Laboratory of Air Traffic Management System Nanjing210000China National Airspace Management Center Beijing100094China

Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex *** methods,while effective in controlled environments,often fail in scenarios involving long-range targets,high noise levels,or intricate backgrounds,highlighting the need for more robust *** address these challenges,we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target *** framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty *** utilizing uncer-tainty predictions,our method refines segmentation outcomes,achieving superior detection ***,this marks the first application of uncertainty modeling within the context of infrared UAV target *** evaluations on three publicly available infrared UAV datasets demonstrate the effectiveness of the proposed *** results reveal significant improvements in both detection precision and robustness when compared to state-of-the-art deep learning *** approach also extends the capabilities of encoder-decoder convolutional neural networks by introducing uncertainty modeling,enabling the network to better handle the challenges posed by small targets and complex environmental *** bridging the gap between theoretical uncertainty modeling and practical detection tasks,our work offers a new perspective on enhancing model interpretability and *** codes of this work are available openly at https://***/general-learner/UQ_Anti_UAV(acceessed on 11 November 2024).

关键词： Object segmentation uncertainty quantification bayesian convolutional neural network

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IT Risk Analysis Based on Risk Management Using ISO 31000: Case study Registration Application at University XYZ 23

IT Risk Analysis Based on Risk Management Using ISO 31000: C...

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9th International Conference on Industrial and Business engineering, ICIBE 2023

作者： Lubis, Fahdi Saidi Praditha, Villy Satria Lubis, Muharman Safitra, Muhammad Fakhrul Ramadhan, Yumna Zahran Information System Department School of Industrial and System Engineering Telkom University Indonesia Software Engineering Department School of Informatics Telkom University Indonesia

ISBN: (纸本)9798400708824

XYZ University has an Alpha Application used during the registration process for student courses each semester. There must be a hazard in the installation of this information system that could impede the process or functionality of the system;therefore, risk analysis is necessary to avoid troubles. By implementing ISO 31000 at XYZ University, it is believed that the risks associated with implementing Alpha can be reduced. This study uses Fishbone Analysis to identify the possible causes of an issue and then separates the root causes. It can also identify potential solutions to this problem (could be more than one problem). According to ISO 31000, risk analysis results are presented as documentation of potential hazards around the Alpha application, with risks grouped based on their impact. The results of this research will be included in the risk evaluation matrix per ISO 31000 recommendations. The evaluation matrix is divided into low, medium, and high-risk categories. So that universities can take advantage of the findings of this risk analysis to prevent and reduce risks and treat them based on the potential impact or risk priority in the Alpha application. Strengthening internal security systems, password policies, encryption, two-factor authentication, and educating students are some ways to mitigate these risks. © 2023 ACM.

关键词： Risk analysis

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