Search Results - political system algorithm
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2024“…To achieve this goal, the successful implementation of an expeditious and reliable optimization algorithm is crucial. To solve this issue, this research proposes an enhanced democratic political algorithm (DPA), which can effectively solve multi-objective optimum power flow problems. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025“…To achieve this goal, the successful implementation of an expeditious and reliable optimization algorithm is crucial. To solve this issue, this research proposes an enhanced democratic political algorithm (DPA), which can effectively solve multi-objective optimum power flow problems. …”
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An initial state of design and development of intelligent knowledge discovery system for stock exchange database
Published 2004“…Data mining is a challenging matter in research field for the last few years.Researchers are using different techniques in data mining.This paper discussed the initial state of Design and Development Intelligent Knowledge Discovery System for Stock Exchange (SE) Databases. We divide our problem in two modules.In first module we define Fuzzy Rule Base System to determined vague information in stock exchange databases.After normalizing massive amount of data we will apply our proposed approach, Mining Frequent Patterns with Neural Networks.Future prediction (e.g., political condition, corporation factors, macro economy factors, and psychological factors of investors) perform an important rule in Stock Exchange, so in our prediction model we will be able to predict results more precisely.In second module we will generate clustering algorithm. …”
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Leveraging Web Scraping in Predictive Modelling of Supply Risk Detection
Published 2022“…The significance of the extracted output is evaluated with the topic modelling algorithm (LDA model algorithm) for the purpose of predictive supply risk. …”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase
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The AI-Driven Transformative Potential of the Gaming Industry for Economy and Society
Published 2024“…It synthesizes technical and humanities disciplines such as artificial intelligence (AI), virtual reality, behavioral psychology, cognitive science, design, agent-based modeling, scenario planning, Foresight, complex systems science, and others. The paper explores the prospects of expanding this interdisciplinary field through the application of more sophisticated technologies, including AI algorithms. …”
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Application of Artificial Intelligence In Smart City
Published 2021“…In Sociological and Political dimensions, the proposed trends are the clear definition of liability of relevant parties, lawfully-regulated-transparency of the AI models, and the cyber-attack rapid-sensing smart security system. …”
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Pemodelan data indeks komposit Kuala Lumpur menggunakan neurofuzzy
Published 2006“…Therefore, in this study, a Hybrid Neurofuzzy approached using Adaptive Neurofuzzy Inference System (ANFIS) model is suggested to predict the behaviour of the Indices. …”
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A proposed model for text and image encryption using different techniques
Published 2023“…This is because of its great importance in all fields related to daily life, whether political, economic, and other aspects change. In this research paper, a new intelligent system that concentrates on image and text encryption and decryption is proposed. …”
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Software agent as an effective tool for managing the Internet of thing data complexity
Published 2017“…On top of that, the existing analysis tools and algorithms did not consider the data generated by sensory devices connected to the Internet. …”
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Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model
Published 2024“…Despite its standard annual computation, impeded by logistical hurdles and the gradual transformation of income inequality, we suggest that short-term forecasting of the Gini coefficient could offer instantaneous comprehension of shifts in income inequality during swift transitions, such as variances due to seasonal employment patterns in the expanding gig economy. System Identification (SI), a methodology utilized in domains like engineering and mathematical modeling to construct or refine dynamic system models from captured data, relies significantly on the Nonlinear Auto-Regressive (NAR) model due to its reliability and capability of integrating nonlinear functions, complemented by contemporary machine learning strategies and computational algorithms to approximate complex system dynamics to address these limitations. …”
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