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  • Open Access

    ARTICLE

    Unleashing the Power of Multi-Agent Reinforcement Learning for Algorithmic Trading in the Digital Financial Frontier and Enterprise Information Systems

    Saket Sarin1, Sunil K. Singh1, Sudhakar Kumar1, Shivam Goyal1, Brij Bhooshan Gupta2,3,4,8,*, Wadee Alhalabi5, Varsha Arya6,7

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3123-3138, 2024, DOI:10.32604/cmc.2024.051599 - 15 August 2024

    Abstract In the rapidly evolving landscape of today’s digital economy, Financial Technology (Fintech) emerges as a transformative force, propelled by the dynamic synergy between Artificial Intelligence (AI) and Algorithmic Trading. Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning (MARL) and Explainable AI (XAI) within Fintech, aiming to refine Algorithmic Trading strategies. Through meticulous examination, we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm, employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions. These AI-infused Fintech platforms harness collective intelligence More >

  • Open Access

    REVIEW

    Multi-Aspect Critical Assessment of Applying Digital Elevation Models in Environmental Hazard Mapping

    Maan Habib1,*, Ahed Habib2, Mohammad Abboud3

    Revue Internationale de Géomatique, Vol.33, pp. 247-271, 2024, DOI:10.32604/rig.2024.053857 - 07 August 2024

    Abstract Digital elevation models (DEMs) are essential tools in environmental science, particularly for hazard assessments and landscape analyses. However, their application across multiple environmental hazards simultaneously remains in need for a multi-aspect critical assessment to promote their effectiveness in comprehensive risk management. This paper aims to review and critically assess the application of DEMs in mapping and managing specific environmental hazards, namely floods, landslides, and coastal erosion. In this regard, it seeks to promote their utility of hazard maps as key tools in disaster risk reduction and environmental planning by employing high-resolution DEMs integrated with advanced More >

  • Open Access

    ARTICLE

    Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

    Xiaoqin Ma1,2, Jun Wang1, Wenchang Yu1, Qinli Zhang1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2063-2083, 2024, DOI:10.32604/cmc.2024.049147 - 15 May 2024

    Abstract The presence of numerous uncertainties in hybrid decision information systems (HDISs) renders attribute reduction a formidable task. Currently available attribute reduction algorithms, including those based on Pawlak attribute importance, Skowron discernibility matrix, and information entropy, struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values, and attributes with fuzzy boundaries and abnormal values. In order to address the aforementioned issues, this paper delves into the study of attribute reduction within HDISs. First of all, a novel metric based on the decision attribute is introduced to solve… More >

  • Open Access

    ARTICLE

    On Multi-Granulation Rough Sets with Its Applications

    Radwan Abu-Gdairi1, R. Mareay2,*, M. Badr3

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1025-1038, 2024, DOI:10.32604/cmc.2024.048647 - 25 April 2024

    Abstract Recently, much interest has been given to multi-granulation rough sets (MGRS), and various types of MGRS models have been developed from different viewpoints. In this paper, we introduce two techniques for the classification of MGRS. Firstly, we generate multi-topologies from multi-relations defined in the universe. Hence, a novel approximation space is established by leveraging the underlying topological structure. The characteristics of the newly proposed approximation space are discussed. We introduce an algorithm for the reduction of multi-relations. Secondly, a new approach for the classification of MGRS based on neighborhood concepts is introduced. Finally, a real-life More >

  • Open Access

    ARTICLE

    Weighted Forwarding in Graph Convolution Networks for Recommendation Information Systems

    Sang-min Lee, Namgi Kim*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1897-1914, 2024, DOI:10.32604/cmc.2023.046346 - 27 February 2024

    Abstract Recommendation Information Systems (RIS) are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet. Graph Convolution Network (GCN) algorithms have been employed to implement the RIS efficiently. However, the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning process. To address this issue, we propose a Weighted Forwarding method using the GCN (WF-GCN) algorithm. The proposed method involves multiplying the embedding results with different weights for each hop layer during graph… More >

  • Open Access

    REVIEW

    An Overview of Modern Cartographic Trends Aligned with the ICA’s Perspective

    Maan Habib1,*, Maan Okayli2

    Revue Internationale de Géomatique, Vol.32, pp. 1-16, 2023, DOI:10.32604/rig.2023.043399 - 30 September 2023

    Abstract This study provides a comprehensive overview of modern cartography innovations and emerging trends, highlighting the importance of geospatial representation in various fields. It discusses recent advancements in geospatial data collection techniques, including satellite and aerial imagery, Light Detection and Ranging (LiDAR) technology, and crowdsourcing. The research also investigates the integration of big data, machine learning, and real-time processing in Geographic Information Systems (GIS), as well as advances in geospatial visualization. In addition, it examines the role of cartography in addressing global challenges such as climate change, disaster management, and urban planning in line with the More >

  • Open Access

    ARTICLE

    Attribute Reduction for Information Systems via Strength of Rules and Similarity Matrix

    Mohsen Eid1, Tamer Medhat2,*, Manal E. Ali3

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1531-1544, 2023, DOI:10.32604/csse.2023.031745 - 03 November 2022

    Abstract An information system is a type of knowledge representation, and attribute reduction is crucial in big data, machine learning, data mining, and intelligent systems. There are several ways for solving attribute reduction problems, but they all require a common categorization. The selection of features in most scientific studies is a challenge for the researcher. When working with huge datasets, selecting all available attributes is not an option because it frequently complicates the study and decreases performance. On the other side, neglecting some attributes might jeopardize data accuracy. In this case, rough set theory provides a… More >

  • Open Access

    ARTICLE

    An Optimized Method for Accounting Information in Logistic Systems

    Ahmad Mohammed Alamri1, Ahmad Ali AlZubi2,*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1595-1609, 2023, DOI:10.32604/csse.2023.027971 - 03 November 2022

    Abstract In the era of rapid information development, with the popularity of computers, the advancement of science and technology, and the ongoing expansion of IT technology and business, the enterprise resource planning (ERP) system has evolved into a platform and a guarantee for the fulfilment of company management procedures after long-term operations. Because of developments in information technology, most manual accounting procedures are being replaced by computerized Accounting Information Systems (AIS), which are quicker and more accurate. The primary factors influencing the decisions of logistics firm trading parties are investigated in order to enhance the design… More >

  • Open Access

    ARTICLE

    An Optimized Method for Information System Transactions Based on Blockchain

    Jazem Mutared Alanazi, Ahmad Ali AlZubi*

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2289-2308, 2023, DOI:10.32604/iasc.2023.029181 - 19 July 2022

    Abstract Accounting Information System (AIS), which is the foundation of any enterprise resource planning (ERP) system, is often built as centralized system. The technologies that allow the Internet-of-Value, which is built on five aspects that are network, algorithms, distributed ledger, transfers, and assets, are based on blockchain. Cryptography and consensus protocols boost the blockchain platform implementation, acting as a deterrent to cyber-attacks and hacks. Blockchain platforms foster innovation among supply chain participants, resulting in ecosystem development. Traditional business processes have been severely disrupted by blockchains since apps and transactions that previously required centralized structures or trusted… More >

  • Open Access

    ARTICLE

    Modernization Framework to Enhance the Security of Legacy Information Systems

    Musawwer Khan1, Islam Ali1, Wasif Nisar1, Muhammad Qaiser Saleem2, Ali S. Ahmed2, Haysam E. Elamin3, Waqar Mehmood4, Muhammad Shafiq5,*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 543-555, 2022, DOI:10.32604/iasc.2022.016120 - 26 October 2021

    Abstract Due to various issues such as lack of agility, low performance, security issues, and high maintenance costs, the organization replaces its legacy information system (LIS). However, with the expansion of information technology, the security of the old system has received great attention. The protection of legacy data and information is critical to the organization. However, achieving safety through modernization, redevelopment, or redesign of LIS is a time-consuming and costly solution, especially in small and medium enterprises (SMEs). In addition, newly developed systems often lose inherent business rules, data integrity, and user trust. In this paper,… More >

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