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Predictive and Comparative Analysis on Products Demand in Supply Chain and Management
2018
Journal of Independent Studies and Research - Computing
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In this study, the dataset of a supermarket located in Pakistan is used which comprises of the actual demand of the past year. ...
The efficient demand forecast system is a useful method to accomplish prior goals, improve customer satisfaction and reduce out of stock conditions for products. ...
Whang, "Information Sharing in a Supply Chain", Stan. Grad. Sch. Bus., Work. Pap. no. 1549, pp. 1-20, 2001. ...
doi:10.31645/jisrc/(2018).16.1.05
fatcat:3mrjcc6xiffkvgx6jwuajitbzu
Comparative analysis of short-term demand predicting models using ARIMA and deep learning
2021
International Journal of Power Electronics and Drive Systems (IJPEDS)
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The experimentations are carried out using a real-life dataset provided by a supermarket in Morocco. ...
Demand prediction is a crucial component in the supply chain's process that allows each member to enhance its performance and its profit. ...
[3] uses ARIMA to reduce demand uncertainty in a blood platelet supply chain. Ji et al. [4] uses a hybrid ARIMA and deep neural network model to forecast future prices of carbon. Matyjaszek et al ...
doi:10.11591/ijece.v11i4.pp3319-3328
fatcat:mfjct7mecbajvnl2r7hbaawsp4
Short-Term Energy Forecasting Framework Using an Ensemble Deep Learning Approach
2021
IEEE Access
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[23, 24] developed a forecasting model for the supermarket by using humidity, temperature, and relative humidity climate variables. ...
In [36] the authors introduced a hybrid approach using radial neural network and stochastic for shortterm energy forecasting and compared the results of this system with MLP to validate the system. ...
doi:10.1109/access.2021.3093053
fatcat:oujwtngnabadhchz4w3bh5veza
Development of Lean Hybrid Furniture Production Control System based on Glenday Sieve, Artificial Neural Networks and Simulation Modeling
2018
Drvna industrija
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Santin et al. (2015) suggest an approach of minimizing the difference between production and demand based on ABC analysis and forecasting sales volumes on a quarterly basis implemented in the MRP system ...
designed control system to these occurrences), two paths should be used for the production systems: 1. for green products stream -Replenishment Pull System used in the main production line; 2. for blue ...
doi:10.5552/drind.2018.1747
fatcat:6efz45xy2rhrxots3jjy3juxke
Availability of material streams in hybrid push/pull shop floor control system
2014
IFAC Proceedings Volumes
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The goal of the research was increasing availability of material in production system for multi-assortment production cells fed with hybrid pull/push strategy. ...
The research is based on demand analysis of a large industrial company providing a wide range of assortment of about 150 final products manufactured according to made-to-order and make-tostock strategy ...
However, practically, hybrid systems are often used, as they benefit from combination of two or more types of systems. What is an expert system then? ...
doi:10.3182/20140824-6-za-1003.02250
fatcat:7vhxqs27yrfmteb2w3dz4z7dre
Purchase-driven Classification for Improved Forecasting in Spare Parts Inventory Replenishment
2010
International Journal of Computer Applications
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Advances in data mining application systems have given rise to the use of business intelligence in various domains of retailing. ...
The model developed in this work suggests a technique for forecasting of demands which results in improved performance of inventory. ...
INTRODUCTION Retail inventory management systems have grown significantly during the last two decades with the advent in intelligent systems for forecasting. ...
doi:10.5120/1507-2025
fatcat:chkfjpinnnfvzaxzwjncyabbgm
Computational Intelligence in the hospitality industry: A systematic literature review and a prospect of challenges
2021
Applied Soft Computing
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We have studied the different approaches on the various forecasting methods and subareas where CI is currently being used. ...
This research work presents a detailed survey about Computational Intelligence (CI) applied to various Hotel and Travel Industry areas. ...
Additionally, in [128] a hybrid SVR method is used to forecast non-stationary power demand. ...
doi:10.1016/j.asoc.2021.107082
fatcat:b6oavdvehvaabcsd2vhypmgafu
A Survey on Electric Power Consumption Prediction Techniques
2020
International journal of engineering research and technology
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distribution from the power system. ...
In the recent time, the demand of accurate electric power consumption prediction has been increased and is considered as an integral part for electric utility in planning and scheduling of electricity ...
This indicated that the hybrid model produces a less forecasting error and can be used for mid-term forecasting along with observed air temperature data.
B. Vincenzo et. al. (2013)
W. J. ...
doi:10.37624/ijert/13.10.2020.2568-2575
fatcat:vjsywz5tivelzozhvapbqqyhta
Qualitative phase space reconstruction analysis of supply-chain inventor time series
2010
South African Journal of Science
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In this paper, we considered a supply-chain (SC) system including several kinds of products. ...
Quantitative methods can forecast the quantitative SC demands, but they cannot indicate the qualitative aspects of SC, so when we apply quantitative methods to a SC system we get only numerous data of ...
Each time point in Figure 2 represents one demand data for each day and we made a demand forecast based on the last 20 days, which was then used to compare the real demand quantity and the forecasted ...
doi:10.4102/sajs.v106i11/12.422
fatcat:glbcb72h2fgm3ncrlagltyicxa
A Framework for Intelligent Inventory Prediction in Small and Medium- Scale Enterprise
2021
European Journal of Business and Management
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Forecasted average demand of items for ten months in a small-scale retail outlet was collected and trained using an Artificial Neural Networks (ANN) of 5 neurons in the input layer with eight neurons in ...
Data collection in a small-scale outlet is a daunting task as record keeping is hardly done. ...
In doing so, an artificial intelligence system is modelled using ANN which is trained on the forecasted data on-demand rate of 15 items collected for ten months in a small and medium scale business retail ...
doi:10.7176/ejbm/13-2-03
fatcat:7x5n6txe3nhwpesr3h546y5cgu
Technology Enabled Customer Relationship Management in Supermarket Industry in Nigeria
2013
American Journal of Industrial and Business Management
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While the modern CRM strategy is intensive in the use of analytical technologies, the Nigeria supermarket industry still at the first stage of its development phase have largely interacted with customers ...
Because customers differ in their preferences and purchasing habit, and their mobility is enhanced by increasing availability of information, firms invest in technologies that help them gain detailed understanding ...
[4] conceptualized this development as a changing system of demand for and supply of supermarket services. ...
doi:10.4236/ajibm.2013.32027
fatcat:7t26ylcsvvhr3nbssoj4gpmzra
A Suitable Artificial Intelligence Model for Inventory Level Optimization
2016
Trendy Ekonomiky a Managementu
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Scientific aim: The effort is directed at finding whether the method of prediction using artificial neural networks is suitable as a tool for enhancing the ordering system of an enterprise. ...
As an instrument for neural network forecasting MathWorks MATLAB Neural Network Tool was used. Deductive quantitative methods for research are also used. ...
Acknowledgment This paper was supported by grant FP-S-15-2787 "Effective Use of ICT and Quantitative Methods for Business Processes Optimization" from the Internal Grant Agency at Brno University of Technology ...
doi:10.13164/trends.2016.25.48
fatcat:fwzleevgtraxnf5d3zr2smtzla
Comparison of Time Series ARIMA Model and Support Vector Regression
2020
International Journal of Hybrid Information Technology
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Knowing and tracking the sales of a business proves useful in all data-driven decisions made from inventory management to shelf layouts in a supermarket. ...
We conclude that support vector regression produces better results in comparison with time series analytics on all datasets used in this paper. ...
[17] used a hybrid sales forecasting model through the combination of a variable selection method and support vector regression in order to forecast the sales of computer products. ...
doi:10.21742/ijhit.2020.13.1.02
fatcat:75hwy37gkvavbcgiwefu553i5q
Demand Forecasting of Retail Sales Using Data Analytics and Statistical Programming
2020
Management şi Marketing
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This paper argues that data analytics can play a critical role in contemporary logistics and especially in demand data management and forecasting of retail distribution networks. ...
The authors utilize the power of 'R', a statistical programming language, which is well-equipped with a multitude of libraries for this purpose, to compare demand forecasting methods and identify the one ...
Many hybrid models are recorded in literature combining ARIMA and ANNs such as the ones by Aburto and Weber (2007) leading to improved forecasting accuracy for a supermarket retail chain or enhancing ...
doi:10.2478/mmcks-2020-0012
fatcat:kefaidbdkbeeviihil6sjgtfde
Next Generation Business Intelligence and Analytics: A Survey
[article]
2017
arXiv
pre-print
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In this survey, we review the evolution of business intelligence systems in full scale from back-end architecture to and front-end applications. ...
Using a uses case from BI in Healthcare, which is one of the most complex enterprises, we show how BI\&A will play an important role beyond the traditional usage. ...
[36] proposed a hybrid machine learning system with fuzzy neural network on locally chain supermarket data. They method enabled incorporating expert knowledge in the forecasting. ...
arXiv:1704.03402v1
fatcat:u4taz2phbzgknm5bpgxazq7y2e
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