All machine learning procedures consume a mathematical foundation. the aforementioned is applicable to Deep learning, optimization, and any additional Statistics Science processes since Deep Knowledge is a subset of M...
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Pickup and delivery problems are frequently encountered problems in transport companies. this paper presents a variant of the homogeneous vehicle, single-to-single Pickup and Delivery Problem with Time Windows, where ...
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ISBN:
(数字)9783031774324
ISBN:
(纸本)9783031774317;9783031774324
Pickup and delivery problems are frequently encountered problems in transport companies. this paper presents a variant of the homogeneous vehicle, single-to-single Pickup and Delivery Problem with Time Windows, where several vehicles must fulfill transport requests from pickup nodes to delivery nodes, called missions, with associated service level agreements (SLA). A mathematical programming model is proposed to tackle this variant, focused on optimizing the allocation and sequencing of missions to be executed by autonomous vehicles. Numerical experiments are performed comparing instances with missions with long and short SLAs. the results show that the model takes longer to find the optimal solution when the missions have short SLAs and increased difficulty in meeting them if the number of vehicles is limited.
the growing energy demand and the need for sustainable solutions have led to the rise of smart buildings equipped with innovative technologies aimed at optimizing energy use. Machine learning (ML) algorithms play a pi...
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Complex mechanical engineering problems usually have the following stages: problem formulation, conceptual design, embodiment development, detailed design, testing, manufacturing, and quality control. the many tasks i...
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ISBN:
(数字)9783031774324
ISBN:
(纸本)9783031774317;9783031774324
Complex mechanical engineering problems usually have the following stages: problem formulation, conceptual design, embodiment development, detailed design, testing, manufacturing, and quality control. the many tasks in the quality control phase often require significant time commitments of highly skilled personnel to complete successfully. therefore, the application of evolutionary optimization at this stage of production can reduce the engineer's involvement in the development process, thereby reducing the time and cost of the task. this paper explores the possibility of evolutionary algorithms to solve the inverse problem of flaw detection, specifically the reconstruction of defect shapes in a product. the proposed solution addresses one of the most challenging technical problems in flaw detection. Experimental studies on a synthetic example demonstrate that the proposed approach can provide a qualitative reconstruction of various defect shapes, even with a limited number of sound pressure receivers. the results show that sound pressure measurements at 64 points are sufficient to correctly detect a defect located anywhere in space and fully recover its shape. thus, using the defect shape reconstruction problem, the study confirms that evolutionary algorithms can be applied to various engineering problems.
In line withthe Recovery and Resilience Plan, the New Generation Storage (NGS) project aims to establish a sustainable technological value chain. Its main objective is the sustainable manufacture and recovery of batt...
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ISBN:
(数字)9783031774324
ISBN:
(纸本)9783031774317;9783031774324
In line withthe Recovery and Resilience Plan, the New Generation Storage (NGS) project aims to establish a sustainable technological value chain. Its main objective is the sustainable manufacture and recovery of batteries for electric mobility. thus, it was decided to evaluate three open-source optimization tools to identify their strengths and weaknesses, aiming to select the most robust optimization service for the project. In this sense, this paper presents an exploratory study on three open-source optimization tools. the main goal was to assess their performance in solving optimization problems that can be applied to real-world scenarios, like the NGS project. the evaluations were conducted using an N-queens benchmark, applying mixed-integer linear programming (MILP) modeling to validate the computational accuracy of each tool. Moreover, this study compares the performance, scalability, and computational efficiency of these tools to identify the most robust option for optimizing large-scale energy storage systems. the findings not only contribute to the selection of an optimal solver for the NGS project but also offer significant insights into the solver practical applicability in broader real-world scenarios, including industrial optimization and energy resource management.
Synthetic Aperture Radar (SAR) images are usually corrupted by speckle noise, which introduces additional challenges to lossy image compression algorithms. Traditional optical image compression techniques fail to take...
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this paper introduces a seismic-inspired simplified earthquake optimization algorithm inspired by seismic wave propagation principles for solving optimization problems. Proposed algorithm combines exploration with loc...
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Withthe rise of Social Media platforms and new applications, the Rapid Expansion of fake accounts has become an important concern, posing threats to security, privacy and trustworthiness. In response, this research e...
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ISBN:
(纸本)9798350350661;9798350350654
Withthe rise of Social Media platforms and new applications, the Rapid Expansion of fake accounts has become an important concern, posing threats to security, privacy and trustworthiness. In response, this research explores the application of machine learning techniques for the detection and reduction of fake accounts. By utilizing datasets containing, user behavior patterns, network characteristics and various parameters, we explore the efficiency of various machine learningalgorithms in selective genuine users from false ones. this study includes attribute manipulation, model training and evaluation techniques made for the unique challenges of fake account detection. We examine the effects of different features, such as interaction measures, language patterns and network structures on the output of detection models. Systematic testing and validation reveal effective methods for identifying fake accounts, enhancing information security and user trust on online platforms.
Wireless Sensor Networks (WSNs) find extensive applications in environmental monitoring, healthcare, and smart cities. Energy efficiency, however, continues to be a significant challenge withthe limited lifetime of s...
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Simplifying the deployment, management, and maintenance of gadget mastering fashions within the manufacturing environment is a key aim in the swiftly growing system gaining knowledge of environment (MLOps). Intelligen...
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