Search Results - political ((system algorithm) OR (swarm algorithm))

A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour M., Ali Z., Othman M.M., Bo R., Javadi M.S., Ridha H.M., Alrifaey M.

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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour, Masoud, Ali, Zaipatimah, Othman, Muhammad Murtadha, Bo, Rui, Javadi, Mohammad Sadegh, Ridha, Hussein Mohammed, Alrifaey, Moath

“…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer by Alsewari, Abdul Rahman Ahmed, Sinan, Q. Salih

“…In this research, a novel swarm-based metaheuristic algorithm which depends on the behavior of nomadic people was developed, it is called ‘‘Nomadic People Optimizer (NPO)’’. …”
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Genetic programming based machine learning in classifying public-private partnerships investor intention / Ahmad Amin ... [et al.] by Amin, Ahmad, Rahmawaty, Rahmawaty, Lautania, Maya Febrianty, Abdul Rahman, Rahayu

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Tree-based machine learning in classifying reverse migration/ Azreen Anuar, Nur Huzeima Mohd Hussain and Hugh Byrd by Anuar, Azreen, Mohd Hussain, Nur Huzeima, Byrd, Hugh

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An initial state of design and development of intelligent knowledge discovery system for stock exchange database by Che Mat @ Mohd Shukor, Zamzarina, Khokhar, Rashid Hafeez, Md Sap, Mohd Noor

“…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 by Ng, Shi Ya

“…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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A new "Mammy" in the age of digitalization; human insecurity versus utopian affective algorithms in Kazuo Ishiguro's Klara and The Sun by Mohamed Ahmed, Alshaymaa Mohamed

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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

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The AI-Driven Transformative Potential of the Gaming Industry for Economy and Society by Yi Qin, Tee, Abdullah, Nor Hazana, Mohd Emran, Natrah

“…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 by Law, Jia Wei

“…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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Classification of stock market index based on predictive fuzzy decision tree by Khokhar, Arashid Hafeez

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Pemodelan data indeks komposit Kuala Lumpur menggunakan neurofuzzy by Mohd. Yunos, Zuriahati

“…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 by Shawkat S.A., Al-Barazanchi I.

“…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. …”

Software agent as an effective tool for managing the Internet of thing data complexity by Mustafa, M.B., Yusoof, M.A.M.

“…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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Ethical Considerations in the Use of AI in Learning and Teaching for Special Education. by Noor Aida, Md Noor, Siti Noor Aneeis, Hashim, Juereanor, Mat Jusoh, Leha, Saliman, Shazali, Johari, NorHamidah, Ibrahim, Zaim Azizi, Abu Bakar, Mohd Norazmi, Nordin

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Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model by Megat Syahirul Amin, Megat Ali, Azlee, Zabidi, Nooritawati, Md Tahir, Ihsan, Mohd Yassin, Eskandari, Farzad, Azlinda, Saadon, Mohd Nasir, Taib, Abdul Rahim, Ridzuan

“…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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