Forecasting ATM cash demands using a local learning model of cerebellar associative memory network

Teddy, S. D.; Ng, See Ket

doi:10.1016/j.ijforecast.2010.02.013

Cited by 34 publications

(14 citation statements)

References 29 publications

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“…In the literatures, techniques used for cash demand forecasting can be broadly classified into four groups [5][6][7][8]:…”

Section: Existing Methods For Cash Forecastingmentioning

confidence: 99%

A Methodology to Improve Cash Demand Forecasting for ATM Network

Darwish¹

2013

IJCEE

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Abstract-Developing cash demand forecasting model for ATM network is a challenging task as the chronological cash demand for every ATM fluctuates with time and often superimposed with non-stationary behavior of users. In order to improve the forecasting precision of ATM cash demand, an Interval Type-2 Fuzzy Neural Network (IT2FNN) has been utilized in this paper. The antecedent parts in each rule of the IT2FNN are interval type-2 fuzzy sets in view of conditions regarding time, location, cash residual and other factors that could lead to consider cash upload able to keep cash at the right levels to meet user demand. The employed IT2FNN has both on-line structure and parameter learning abilities. Simulation results for ATM cash forecasting show the feasibility and effectiveness of the proposed method.

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“…In the literatures, techniques used for cash demand forecasting can be broadly classified into four groups [5][6][7][8]:…”

Section: Existing Methods For Cash Forecastingmentioning

confidence: 99%

A Methodology to Improve Cash Demand Forecasting for ATM Network

Darwish¹

2013

IJCEE

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“…Armenise, Birtolo, Sangianantoni, and Troiano (2010) used a specific genetic algorithm. Teddy and Ng (2011) forecasted the cashdemands with the help of cerebellar associative memory network, Ekinci, Lu, and Duman (2015) used group-demand forecasts. Baker, Jayaraman, and Ashley (2013) dropped the assumption of normally distributed errors to improve the cash demand forecast.…”

Section: Relevant Literature On Cash Managementmentioning

confidence: 99%

Pareto improvement and joint cash management optimisation for banks and cash-in-transit firms

Ágoston

Benedek

Gilányi

2016

European Journal of Operational Research

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Available online xxx Keywords:OR in banking Cash-management Group decisions and negotiations Supply chain management a b s t r a c t Improving the ATM cash management techniques of banks has already received significant attention in the literature as a separate optimisation problem for banks and the independent firms that supply cash to automated teller machines. This article concentrates instead on a further possibility of cost reduction: optimising the cash management problem as one single problem. Doing so, contractual prices between banks and the cash in transit firms can be in general modified allowing for further cost reduction relative to individual optimisations. In order to show the pertinence of this procedure, we have determined possible Pareto-improvement re-contracting schemes based on a Baumol-type cash demand forecast for a Hungarian commercial bank resulting in substantial cost reduction.

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“…Other work for NN5 Competition data includes Coyle (2009) who developed a model based on the self-organizing fuzzy neural network, and Wichard (2010) who utilized forecast combination via a simple average idea for improving forecasting quality. Teddy and Ng (2011) reconstructed missing values in the raw data using the weighted average of the last and the next known withdrawal records in the series. Ben Taieb et al (2012) considered the effects of seasonality, input variable selection, and forecast combination.…”

Section: Literature Reviewmentioning

confidence: 99%