Résultats de la recherche - optimization algorithm

Given resource constraints, the need to minimize water access time, and the prevention of shortages, optimizing the distribution and density of water resources is considered a fundamental requirement for effective crisis management of fire following earthquakes (FFE). While no comprehensive and opti...

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To address the issues of high energy consumption, low thermal comfort, and excessive greenhouse gas emissions in residential buildings, this study optimizes multi-story residential buildings in the Suzhou region using a multi-objective Non-dominated Sorting Genetic Algorithm III (NSGA-III) coupled w...

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Traditional Economic Dispatch (ED) models are designed for scenarios with stable and abundant fuel supplies; therefore, they are not inherently tuned to handle fuel shortages. To ensure robust and efficient power management, the traditional ED must be modified to address these challenges. This artic...

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Diabetes has been recognized as a major cause of death. Diabetes is a chronic disease. In recent years, the impact of diabetes has increased dramatically, and it has become a global threat. Machine learning is a part of computational algorithms designed to imitate human intelligence by learning from...

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The article systematizes modern ideas about the features of using artificial intelligence tools in order to analyze and optimize financial flows. The relevance of the topic is argued by the rapid growth in the volume of transactions in the global economy, combined with the inability of traditional m...

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To tackle the challenge of data diversity in sentiment analysis and improve the accuracy and generalization ability of sentiment analysis, this study first cleans, denoises, and standardizes multi-source data, and then proposes an improved sentiment analysis framework based on deep transfer learning...

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The accurate inversion of mining subsidence prediction parameters is key to the precise prediction of deformation during mining. However, the use of traditional genetic algorithms (GA) for inversion prediction has problems such as poor resistance to differences, and the accuracy of inversion paramet...

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The use of inverse modeling-based crossover operators in multi-objective evolutionary algorithms (MOEAs) has recently received much attention. Sampling in the objective space is advantageous over sampling in the decision space as it allows selecting promising areas worthy to explore. This paper aims...

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Currently, deep reinforcement learning has been widely applied to energy system optimization and scheduling, and the DRL method relies more heavily on historical data. The lack of historical operation data in new integrated energy systems leads to insufficient DRL training samples, which easily trig...

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Intrusion Detection Systems (IDS) play a key role in protecting modern network infrastructures from malicious activities in the internet of sensor things domain. However, the presence of class imbalance, limited labeled data, and the need for hyperparameter tuning frequently restricts the overall ef...

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[Objective] To minimize passenger travel time while reducing operational costs for enterprises, it is necessary to identify an optimal balance between these two competing objectives. A systematic study on the stop plan for express/local trains on city rapid rail transit lines should be conducted bas...

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A set of models of feedforward neural networks is created to obtain operational forecasts of the time series of the hryvnia/dollar exchange rate. It is shown that using an evolutionary algorithm for the total search of basic characteristics and a genetic algorithm for searching the values of the ma...

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This paper proposes a comprehensive Mixed-Integer Linear Programming (MILP) formulation for the simultaneous scheduling of machines and Automated Guided Vehicles (AGVs) within a partitioned Flexible Manufacturing System (FMS). The main objective is to numerically optimize the simultaneous scheduling...

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The artificial lighting based on multiple-primary light-emitting diodes (LEDs) or multiple-primary laser diodes (LDs) makes the diversity of colors by freely and simply adjusting the emission spectra of rays from these semiconductor devices. It brings the possibility that the artificial lighting mat...

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In project management, a project is typically described as an activity-on-edge network, where each activity/job is represented as an edge of some network <i>N</i> (which is a directed acyclic graph). To speed up the project (i.e., reduce the duration), the manager can crash a few jobs (n...

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With the rapid development of electric vehicles，V2G technology can greatly reduce the energy cost of users in the home energy management system，but V2G will affect user travel. This paper proposes an optimization strategy for home energy management system based on users' commuting behavior....

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Urban block configuration significantly impacts outdoor thermal comfort (OTC). While many studies have examined the effects of individual variables such as building orientation and the height-to-width ratio (H/W) on OTC, there has been limited systematic optimization of multiple configuration variab...

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The catalytic synthesis of methanol from hydrogen and carbon dioxide is the key to solving the technical problem of "production, storage, transportation, addition, and utilization" of hydrogen energy. This study highlights a mathematical model of generalized energy storage for methanol syn...

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Unmanned Aerial Vehicles (UAVs) are increasingly used in the new generation of communication systems. They serve as access points, base stations, relays, and gateways to extend network coverage, enhance connectivity, or offer communications services in places lacking telecommunication infrastructure...

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Optimal energy hub scheduling (EHS) has emerged as a promising strategy for improving the efficiency and flexibility of power systems. Energy hubs (EHs) offer several advantages over conventional power grids, including enhanced flexibility, reduced emissions, and improved efficiency. However, EHS po...

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