The Crystal Ball: Predictive Analysis

1977 ◽  
Vol 22 (1) ◽  
pp. 19-21
Author(s):  
LLOYD H. STRICKLAND

1980 ◽  
Vol 41 (C10) ◽  
pp. C10-281-C10-293 ◽  
Author(s):  
R.S. Simon
Keyword(s):  

2019 ◽  
Vol 13 (1) ◽  
pp. 27-36
Author(s):  
Andreas Neubert

Due to the different characteristics of the piece goods (e.g. size and weight), they are transported in general cargo warehouses by manually-operated industrial trucks such as forklifts and pallet trucks. Since manual activities are susceptible to possible human error, errors occur in logistical processes in general cargo warehouses. This leads to incorrect loading, stacking and damage to storage equipment and general cargo. It would be possible to reduce costs arising from errors in logistical processes if these errors could be remedied in advance. This paper presents a monitoring procedure for logistical processes in manually-operated general cargo warehouses. This is where predictive analysis is applied. Seven steps are introduced with a view to integrating predictive analysis into the IT infrastructure of general cargo warehouses. These steps are described in detail. The CRISP4BigData model, the SVM data mining algorithm, the data mining tool R, the programming language C++ for the scoring in general cargo warehouses represent the results of this paper. After having created the system and installed it in general cargo warehouses, initial results obtained with this method over a certain time span will be compared with results obtained without this method through manual recording over the same period.


2010 ◽  
Vol 4 (4) ◽  
pp. 33-39 ◽  
Author(s):  
Thomas Page ◽  
Gisli Thorsteinsson

2017 ◽  
Vol 3 (2) ◽  
pp. 112
Author(s):  
Patrícia Regina da Silva Zaluski ◽  
Maria José Pereira Dantas
Keyword(s):  

Neste artigo a Simulação de Monte Carlo (SMC) é aplicada de forma a exemplificar seu uso, avaliando o comportamento dos diferentes tipos de aviários em atender demandas simuladas, com base nas variáveis de preço e custo aplicados à indústria e produtor. O modelo foi implementado em Excel com o apoio do suplemento Crystal Ball. Ao final do artigo pode-se observar o comportamento dos subprodutos do frango de corte sob regime dos diferentes níveis de tecnologia de aviários. Concluiu-se que os aviários climatizados positivo e negativo apresentam semelhanças nos resultados alcançados na simulação, o que demonstra uma baixa relação custo/benefício no investimento em aviários climatizados negativos, pois necessitam de investimento inicial elevado. Este artigo considera uma análise superficial, contemplando apenas uma parcela do cenário real existente ao produtor.


Author(s):  
Yogesh Awasthi

Agriculture is the backbone of the developing country. In old era agriculture was based on the experience which was shared by people to people but in this digital era technology play a very important and significant role in agriculture. Now agriculture become a business hub therefore farmers are focusing on precision farming. They introduced the technology in agriculture to define the accurate information about seed, soil, weather, disease and all factors which affecting the farming. Artificial Intelligence uses predictive analysis, image analysis, learning techniques and Pattern analysis to declare the best cost effective and maximum gain for the agriculturist. The aim of this paper is to provide the crucial information with the help of technology which a farmers can use to harvest the variety of crops as per the demand in world so that they can get maximum benefits.


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