Results 41 to 50 of about 394,967 (298)
Genetic algorithms in seasonal demand forecasting [PDF]
, 2000 The method of forecasting seasonal demand applying genetic algorithm is presented. Specific form of used demand function is shown in the first section of the article.
Chodak, Grzegorz, Kwaśnicki, Witold
core
Sparse Regularization in Marketing and Economics
, 2018 Sparse alpha-norm regularization has many data-rich applications in Marketing and Economics. Alpha-norm, in contrast to lasso and ridge regularization, jumps to a sparse solution.
Feng, Guanhao +3 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Pulmonary dysfunction and sleep abnormalities are common in children with sickle cell disease (SCD) and are associated with worse clinical outcomes. Whether spirometry abnormalities are associated with polysomnography (PSG) findings remains unclear.
Ammar Saadoon Alishlash +4 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Families of children with cancer experience significant financial strain, even with universal healthcare. Indirect costs, such as productivity losses and non‐medical expenses, are rarely included in economic evaluations, and little is known about how effectively financial aid programmes alleviate this burden. Childhood brain tumours
Megumi Lim +8 more
wiley +1 more source
Forecasting intermittent demand [PDF]
, 2006 Methods for forecasting intermittent demand are compared using a large data-set from the UK Royal Air Force (RAF). Several important results are found.
Duncan, L, Teunter, R H
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background 131I‐metaiodobenzylguanidine (131I‐MIBG) radiotherapy is a key treatment for relapsed and refractory (R/R) neuroblastoma (NB). Patients with R/R disease treated in the modern era are increasingly exposed to anti‐GD2 immunotherapy, which exerts selective pressure and may modify both tumor cell state and microenvironment.
Benjamin J. Lerman +7 more
wiley +1 more source
Intermittent Demand Forecasting for Spare Parts Using Artificial Neural Networks and Deep Learning: Literature Review [PDF]
JES: Journal of Engineering SciencesForecasting Intermittent demand for spare parts is essential for enhancing inventory management, particularly in industries where unplanned equipment downtime and inventory holding costs are significant.
Omnia Nabil, Nahid Afia, T Ismail
doaj +1 more source
Spatial-Temporal Correlation Neural Network for Long Short-Term Demand Forecasting During COVID-19
IEEE Access, 2023 Demand forecasting is an important method for dealing with the supply-demand relationship in social resource management. The demands of daily life discussed in this study are mainly about hotels, restaurants, gas stations, drugstores, shopping malls, etc.
Xiaochuan Guo, Wenbo Xie, Xin Li
doaj +1 more source
THE INFLUENCE OF ADVERTISING ON THE DEMAND FORECASTING [PDF]
, 2012 This paper deals with the notion of approximate probabilistic bisimulation (APB) relation for discrete-time labeled Markov Chains (LMC). In order to provide a quantified upper bound on a metric over probabilistic realizations for LMC, we exploit the ...
Abate, Alessandro +2 more
core +1 more source
Leveraging Elastic Demand for Forecasting [PDF]
2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA), 2019 Demand variance can result in a mismatch between planned supply and actual demand. Demand shaping strategies such as pricing can be used to shift elastic demand to reduce the imbalance. In this work, we propose to consider elastic demand in the forecasting phase.
Houtao Deng +3 more
openaire +2 more sources