An Efficient Novel Approach on Machine Learning Paradigmsfor Food Delivery Company through Demand Forecastıng in societal community

Abstract

A food delivery business must be able to accurately forecast demand on a daily and weekly basis since it deals with a lot of perishable raw components. A warehouse that keeps too much inventory runs the danger of wasting items, whereas a warehouse that maintains too little inventory runs the risk of running out of stock, which might lead consumers to switch to your competitors. Planning for purchasing is essential because most raw materials are perishable and delivered on a weekly basis. For this issue to be resolved, demand forecasting is crucial. With the aid of historical data-driven predictive research, demand forecasting determines and forecasts future consumer demand for a good or service. By predicting future sales and revenues, demand forecasting assists the organisation in making more educated supply decisions. Regression methods like linear regression, decision trees, and Xgboost are used to overcome this issue.

Development of a Decision Support System for Perishable Food Management in Culinary Education Institutions Using Machine Learning with Linear Regression

“…These models can assist in accurately forecasting food orders, thereby enabling effective inventory management and waste reduction. (Jayapal, 2022) , (Yerragudipadu et al, 2023) .Quality Monitoring and Inventory Control: The application of machine learning techniques, such as deep reinforcement learning, can contribute to improved inventory management of perishable goods. Additionally, machine learning and fuzzy logic have been employed for quality monitoring and traceability in the food supply chain.…”

“…Machine learning models, including linear regression, can be effectively applied to food demand prediction and quality monitoring, helping to minimize operation costs and reduce food waste. (Yerragudipadu et al, 2023), (Jayapal, 2022. ) .Decision support systems powered by machine learning techniques, such as model-based reinforcement learning, have shown promising results in optimizing inventory management and reducing food waste in the retail sector.…”

A Machine Learning Chronicle in Airfares for Pricing the Clouds

“…Request forecast & value segregation are two instances about computational strategies carriers use towards support income. towards set aside client's cash, two sorts about models have been proposed by various scientists: models certain predict best an open door towards buy a ticket & models certain predict base ticket cost [17][18][19].…”

An Efficient IoT-Based Novel Approach for Fire Detection Through Esp 32 Microcontroller in Forest Areas

“…When temperatures exceed a predetermined threshold, this system uses sensors to detect changes in temperature and warns authorities via a registered mobile number. When a fire occurs, the device will sound a buzzer and alert the authorities as the size of the flame increases [12][13][14]. By using this method, we can avoid or confine fires in order to maintain forests and safeguard species.…”