Forecasting currency exchange rates with an Artificial Bee Colony-optimized neural network

Worasucheep, Chukiat

doi:10.1109/cec.2015.7257305

Cited by 11 publications

(5 citation statements)

References 37 publications

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“…Tools to reduce driving risks can be particularly beneficial for the entire system. [5]. In addition, artificial intelligence and machine learning can be used to predict and detect the risk of fraud, suspicious transactions, late payments, and cyber-attacks, which can lead to better risk management.…”

Section: Review Of Literaturementioning

confidence: 99%

“…Moreover, the application of ML based technologies supports in creating better interaction with the customers and enables addressing their queries in an effective manner. e application of machine learning algorithms in discovering better concepts, analysing the data effectively, and providing the information for taking better financial decisions [5].…”

Section: Introductionmentioning

confidence: 99%

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A Comparative Analysis of Business Machine Learning in Making Effective Financial Decisions Using Structural Equation Model (SEM)

Sujith

Khan

Dornadula³

et al. 2022

Journal of Food Quality

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Globally, organisations are focused on deriving more value from the data which has been collected from various sources. The purpose of this research is to examine the key components of machine learning in making efficient financial decisions. The business leaders are now faced with huge volume of data, which needs to be stored, analysed, and retrieved so as to make effective decisions for achieving competitive advantage. Machine learning is considered to be the subset of artificial intelligence which is mainly focused on optimizing the business process with lesser or no human interventions. The ML techniques enable analysing the pattern and recognizing from large data set and provide the necessary information to the management for effective decision making in different areas covering finance, marketing, supply chain, human resources, etc. Machine learning enables extracting the quality patterns and forecasting the data from the data base and fosters growth; the machine learning enables transition from the physical data to electronically stored data, enables enhancing the memory, and supports with financial decision making and other aspects. This study is focused on addressing the application of machine learning in making the effective financial decision making among the companies; the application of ML has emerged as a critical technology which is being applied in the current competitive market, and it has offered more opportunities to the business leaders in leveraging the large volume of data. The study is intended to collect the data from employees, managers, and business leaders in various industries to understand the influence of machine learning in financial decision making .

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Section: Review Of Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis of Business Machine Learning in Making Effective Financial Decisions Using Structural Equation Model (SEM)

Sujith

Khan

Dornadula³

et al. 2022

Journal of Food Quality

View full text Add to dashboard Cite

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“…Worasucheep [6] Network management e role of SDR in network management is immense and support in the implementation of advanced cognitive radio network.…”

Section: Chi-square Test Analysismentioning

confidence: 99%

Addressing the Real World Problem of Managing Wireless Communication Systems Using Explainable AI-Based Models through Correlation Analysis

Surya

Gupta

Mehbodniya

et al. 2022

Mathematical Problems in Engineering

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In a general parlance, wireless communication tends to be investigated based on the available methods that support enhancing the optimized data link, especially the software-based methods. AI is mainly used to create and design efficient communication network systems and variable node locations. The major factors impacting wireless communications in the current context are enhanced channel frequency, efficiency of using the bandwidth, and modulation type. The software-defined ratio enables collecting the information and analyzing the overall signal-related components and processing them in real-time situations. This will support in detecting unnecessary information and identifying latency at each stage of communication. The study is intended to measure the influence of critical factors in enhancing the overall management of wireless communication systems through the application of AI technologies. The researchers used the questionnaire method in order to collect the data from the respondents and enable them to analyze the data using the SPSS data package.

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“…Ghasemiyeh et al (2017) applies this technique to stock price prediction. Worasucheep (2015) integrate an alternative optimization technique -Artificial…”

Section: Asset Modelling and Forecasting Topicsmentioning

confidence: 99%

Machine Learning and Finance

Khatib¹

2021

Int J Innov Educ Res

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The aim of this paper is provide a first comprehensive structuring of the literature applying machine learning to finance. We use a probabilistic topic modelling approach to make sense of this diverse body of research spanning across the disciplines of finance, economics, computer sciences, and decision sciences. Through the topic modelling approach, a Latent Dirichlet Allocation Technique (LDA), we can extract the 14 coherent research topics that are the focus of the 6,148 academic articles during the years 1990-2019 analysed. We first describe and structure these topics, and then further show how the topic focus has evolved over the last two decades. Our study thus provides a structured topography for finance researchers seeking to integrate machine learning research approaches in their exploration of finance phenomena. We also showcase the benefits to finance researchers of the method of probabilistic modelling of topics for deep comprehension of a body of literature, especially when that literature has diverse multi-disciplinary actors.

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Forecasting currency exchange rates with an Artificial Bee Colony-optimized neural network

Cited by 11 publications

References 37 publications

A Comparative Analysis of Business Machine Learning in Making Effective Financial Decisions Using Structural Equation Model (SEM)

A Comparative Analysis of Business Machine Learning in Making Effective Financial Decisions Using Structural Equation Model (SEM)

Addressing the Real World Problem of Managing Wireless Communication Systems Using Explainable AI-Based Models through Correlation Analysis

Machine Learning and Finance

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