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112 articles for “pricing”
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Price Comparison with Sentimental Analysis
Abstract: The price comparison website is designed to compare the prices of the products from various websites, which will help users to choose products that save money and time through online. Considering the customer's busy life especially those who are living in the city area, most of them prefer online shopping to save their time. Customers always prefer to buy products for low prices and compare prices from different e-commerce websites, …
Published in International Journal of Electronics Automation · Vol. 2, Issue 1, 2024 · pp. 20–27 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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E-Commerce and AI: Product Recommendation and Pricing
Abstract: E-commerce has evolved from a simple online storefront to a complex ecosystem driven by data and demanding personalized experiences. In this highly competitive environment, businesses are continuously looking for new ways to entice and keep customers. Artificial intelligence is growing as an effective instrument, offering a multitude of applications that are transforming the e-commerce industry. This study will look at the important areas wherein AI is having a substantial impact, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 37–45 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 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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SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting
Abstract: This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 61–71 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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A Linear Regression Model Used to Analysis the Tesla Stock Price Prediction Using Machine Learning
Abstract: The stock market is a fascinating sector of the economic research. It comes in a number of varieties. Several specialists have been examining and investigating the several patterns that the stock market experiences fluctuations. Predicting the stock values of different companies using historical data has been one of the primary research projects. Stock price prediction can help people a great deal by helping them understand where and how to invest, …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 2, 2024 · pp. 8–13 Read article
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House Price Prediction Using Linear Regression In Machine Learning
Abstract: In the modern world, real estate is among the most important investments, particularly in a city like Chennai, which is where many people aspire to work and settle down. Due to people's high purchasing power, this will cause property prices to rise daily. When purchasing a home, buyers will consider whether or not it will yield a healthy profit margin. Hence, before spending your hard-earned money on any property, it …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 92–100 Read article
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China’s Economic Performance (2020–2024): A Sectoral Index Analysis
Abstract: This study applies Laspeyres, Paasche, and Fisher ideal indices to China’s official 2020–2024 price and quantity data, quantifying sectoral inflation and real growth in agriculture, manufacturing, services, exports, and investment. Results show manufacturing experienced mild deflation (Laspeyres ≈ 98.7, implying ≈ 1.3% overall price decline) with a slight real output drop (~6.1%). A key driver was a sharp 21.4% fall in electric vehicle unit prices, despite +523% volume growth. Services …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 14, Issue 3, 2025 Read article
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China’s Economic Performance (2020–2024): A Sectoral Index Analysis
Abstract: This study applies Laspeyres, Paasche, and Fisher ideal indices to China’s official 2020–2024 price and quantity data, quantifying sectoral inflation and real growth in agriculture, manufacturing, services, exports, and investment. Results show manufacturing experienced mild deflation (Laspeyres ≈ 98.7, implying ≈ 1.3% overall price decline) with a slight real output drop (~6.1%). A key driver was a sharp 21.4% fall in electric vehicle unit prices, despite +523% volume growth. Services …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 3, 2025 · pp. 26–38 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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Prediction of Mobile Phone Price Using Machine Learning Classifiers
Abstract: One cannot imagine one's life without mobile phones; in today's digital era, mobile phones have become a necessity for everyone to fulfil their various demands like messaging, communication, entertainment, productivity, research, shopping and many more. In a thriving market of mobile phones where new smartphones are launched every year with new advanced features and various designs, determining the expense of a mobile can be a trouble-some tasks for consumers. In …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 101–108 Read article
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Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 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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Identification and Assessment of the Factors causing Cost Overrun in Housing Projects
Abstract: Poor cost performance is a major problem in construction industry, especially in developing countries like India. Statistics reveal that majority of the projects faces the issue of cost overrun. The interrelationship between the causes of cost overrun and stakeholders has not been explored yet. The aim of the research is to minimize the effects of project cost overrun. The objective of the study is to categorize and rank the potential …
Published in International Journal of Urban Design and Development · Vol. 1, Issue 1, 2023 · pp. 17–34 Read article
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Stock Market Analysis Using Data Science
Abstract: Stock market prediction using data science has become a popular area of research and application in recent years. This is because the stock market is a complex system with many variables and factors that affect its behavior, making it difficult to predict with certainty. The stock market has always been the aggression of buyers and sellers of stocks, therefore in the global finance market, stock trading is one of the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 1–4 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