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37 articles for “Dynamic pricing”
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Dynamic Price Model for E-Commerce
Abstract: Retailers may now respond to fluctuating demand, inventory levels, competitor activities, consumer traits, and market circumstances using dynamic pricing, a data-driven technique that has become more significant in e-commerce. Modern pricing systems are much more complex and responsive than they were in the past due to the fast advancements in artificial intelligence (AI), machine learning (ML), big data analytics, and reinforcement learning. This review critically examines recent developments in dynamic …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 2, 2026 · pp. 45–55 Read article
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The Rise of AI in E-Commerce: Transforming Shopping Experiences
Abstract: The field of e-commerce is transforming due to the integration of artificial intelligence, offering businesses fresh possibilities to enhance customer experiences, streamline operations, and foster expansion. This article explores the transformative impact of artificial intelligence (AI) on various aspects of e-commerce, including personalized shopping experiences, intelligent chatbots and virtual assistants, predictive analytics for inventory management, dynamic pricing strategies, visual search and image recognition, fraud detection, and security measures, augmented reality …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 22–26 Read article
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Real-Time Cab Fare and ETA Prediction Using API Integration
Abstract: The exponential proliferation of ride-hailing platforms has necessitated the formulation of sophisticated and highly responsive predictive models for cab fare estimation and estimated time of arrival (ETA) computation. This work elucidates a robust framework leveraging real-time application programming interface (API) integration from Uber and Ola within a Flutter-based ecosystem to enhance predictive analytics. By assimilating real-time geospatial data, dynamic pricing algorithms, and latency-optimized API responses, this study investigates the empirical …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 08–15 Read article
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Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
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Exploratory Analysis of the Statistical Characteristics of Nuclear Fuel Cost Trends
Abstract: Nuclear power reactors of the current fleet mainly use uranium as the fissile fuel material. The economics of nuclear fuels are mainly governed by the prices of uranium. This work is an analysis of monthly uranium price data available from public data sources, covering the time frame from January 1990 to April 2025. In the near term, from 2021 to 2024, monthly uranium spot prices have been between $ 35.28±6.64/lb …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 3, 2025 · pp. 39–49 Read article
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Evaluating Performance of Production Sharing Contract and Concessionary System: An Overview and Assessment Based on Examples from Selected Countries
Abstract: Exploration and production of hydrocarbons in different regions is controlled by regulatory system which is classified in to concessionary and contractual system. The contractual system is further divided in to production sharing and service contracts. Generally, any fiscal system is designed to facilitate maximum benefit to the host government keeping in mind risk taken by the operator in discovering and developing the resources to provide them profitability in oil price …
Published in Journal of Offshore Structure and Technology · Vol. 2, Issue 1, 2015 · pp. 41–54 Read article
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Data Mining for E-Commerce and Social Media: Insights and Future Research Directions
Abstract: The fast expansion of e-commerce and social media has heralded a new era of data-rich settings, with enormous quantities of user interactions, preferences, and transactions generated on a daily basis. Data mining has developed as a critical strategy for leveraging big datasets, allowing businesses to gain concrete knowledge and drive decision-making. Data mining in e-commerce improves operational efficiency and user pleasure by allowing for personalized recommendations, consumer segmentation, fraud detection, …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 1, 2025 · pp. 14–23 Read article
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Strategies for Efficient Integration of Distributed Energy Resources into Microgrid Systems
Abstract: With the growing integration of Distributed Energy Resources into modern power systems, the global energy landscape is changing. Some of the DERs are solar photovoltaic (PV), wind turbines, battery storage systems, combined heat and power (CHP) units, and electric vehicles (EVs). Some of the advantages include lower transmission losses, better energy efficiency, and more resilience to grid failures. However, the far-reaching integration of DERs carries with it considerable technical, economic, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 51–56 Read article
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E-Commerce Study Using AR/VR and Ethical Convergence of Commerce
Abstract: The landscape of E-commerce is undergoing a fundamental transformation, shifting from a platform-centric model of transactional exchange to an immersive, ecosystem-driven experience. This analysis examines the critical trends and disruptive forces that define the immediate and long-term trajectory of digital commerce. The study identifies three foundational pillars driving future growth: Hyper-Personalization via Generative AI, Spatial Commerce (AR/VR Integration), and Sustainable Supply Chain Resilience. Future E-commerce will be characterized by the …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 20–26 Read article
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Random Forrest Based Man-in-the-Middle Attack Detection in Advanced Metering Infrastructure
Abstract: Advanced metering infrastructure (AMI) plays a central role in the operation of modern smart grid (SG) systems by enabling continuous, two-way communication between utility providers and consumers. Through this communication, AMI supports real-time monitoring, dynamic pricing, and efficient energy management. However, the same connectivity that makes AMI effective also increases its exposure to cyber threats. One of the most critical threats is the man-in-the-middle (MITM) attack, in which an attacker …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 1–8 Read article
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AI-Driven Dairy Ledger: Enhancing Efficiency with Machine Learning
Abstract: The dairy business nevertheless has ongoing difficulties with financial management, record-keeping, and operational effectiveness, which frequently lead to resource mismanagement, human mistakes, and revenue losses. These problems are most noticeable on small- to medium-sized farms where manual labor is the primary method. This study introduces an AI-driven Dairy Ledger, a complete machine learning-powered system designed to automate and optimize key dairy functions, such as tracking cow feed orders, managing milk …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 36–46 Read article
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Analysis of Gold Price Trend Using the Hidden Markov Model
Abstract: This study aims to analyze the behavior of gold prices in India through a two-state Hidden Markov Model (HMM). We first formulated crucial parameters, such as the Transition Probability Matrix (TPM), Initial Probability Vector (IPV), and Emission Probability Matrix (EPM). Subsequently, we constructed a hidden Markov probability distribution and evaluated Pearson’s coefficients to gauge the correlations separately for each state. The goodness of fit of the developed model was assessed …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 2, 2024 · pp. 7–16 Read article
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Optimizing Residential Energy Costs with PEV-based Energy Storage and Particle Swarm Optimization
Abstract: This research addresses the critical challenge of optimizing electrical energy usage amidst the increasing integration of variable renewable energy sources and the widespread adoption of electric vehicles (EVs). The core objective is to alleviate the energy cost burden for residential consumers by leveraging the capacity of Plug-in Electric Vehicles (PEVs) as an auxiliary energy source. Through innovative utilization of PEVs for both charging and discharging actions based on dynamic electricity …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 14, Issue 3, 2024 · pp. 19–29 Read article
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Econometric Modeling for Oil Sectors Stock Prices Time Series Data
Abstract: This study examines the dynamic relationships of stock oil prices of different Indian oil sectors viz., Bharat Petroleum, Hindustan Oil Corporation and Oil and Natural Gas Corporation based on the different econometric models. Empirical result shows that the monthly oil prices are non-stationary and integrated of order one. Johanson procedure to test for the possibility of co-integration relationships result shows that there is no co-integration relationship. Since the variables are …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 2, 2018 · pp. 27–34 Read article
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Virtual Machine Cost & Computing comparison between cloud service
Abstract: Cloud computing has revolutionized enterprise IT infrastructure with virtual machines forming the cornerstone of Infrastructure as a Service deployment. This study provides a detailed comparative evaluation of virtual machine pricing and computational performance among three leading cloud computing platforms: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Through quantitative analysis of current pricing data from September 2025, independent performance benchmarks from Cockroach Labs 2021 Report, and market …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 2, 2026 Read article
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AI-Based House Price Prediction
Abstract: The housing market is one of the most dynamic and significant sectors of any economy, influencing both individual wealth and broader economic stability. Buyers, sellers, investors, and policymakers all rely on accurate housing price predictions. With the advent of artificial intelligence (AI) technologies, particularly machine learning algorithms, the task of house price prediction has seen remarkable advancements. This study provides a detailed overview of AI-based techniques for house price prediction. …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 1–7 Read article
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Machine Learning Based House Price Forecasting
Abstract: This research endeavours to craft a predictive model leveraging machine learning to estimate the market value of houses in Delhi. By integrating Python and its powerful libraries, pandas for data processing, Plot for interactive visualizations, scikit-learn for implementing machine learning algorithms, XGBoost for boosting the model's prediction accuracy, and to evaluate the model's performance cross-validation techniques are used. An interactive user interface is created using a Flask web application to …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 5–11 Read article
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Design of an ArUco Marker-Guided Smart Trolley with Integrated Billing Estimation
Abstract: The growing adoption of automation in retail environments has increased the need for intelligent systems that improve user convenience and reduce manual effort. This paper presents the design and development of a human-following smart shopping trolley with an integrated automatic billing system based on computer vision. The proposed system employs ArUco marker–based human tracking to achieve reliable and real-time following behaviour. A Raspberry Pi serves as the central processing unit, …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 55–65 Read article
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Interest Level Prediction in Rental Properties Using Data Science
Abstract: A key component of forecasting home prices and rental patterns is real estate market analysis. Data science, data mining methodologies, and statistical models are some of the strategies that have been created in recent years to solve this problem. A few problems are still required to be resolved, such as the obstacles caused by the availability and quality of the data; the presence of outliers, missing values, and inconsistent formats …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 28–34 Read article
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Scheduled Charging and Discharging of Electric Vehicles for Charging Cost Optimization
Abstract: The growing number of Electric Vehicles (EVs) will have remarkable impacts on the power grid as it leads to the increase in total energy consumption. This increases the overall burden on the grid which would require new power plants. However, it is possible to minimize the impact by proper scheduling for charging and discharging of electric vehicles. In this paper, three optimal schemes have been compared i.e. global optimal scheduling …
Published in Journal of Microelectronics and Solid State Devices · pp. 1–10 Read article