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1
artículo
Publicado 1999
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ARIMA univariate time series analysis were used for modeling and forecasting future energy production and consumption in Asturias-Spain. Initially, each series was recorder monthly from 1980 to 1996. These data include trend and seasonal variations wich allow the use of ARIMA (AutoRegressive Integrated Moving Average) univariate models for predictions of future behavioral patterns. The optimum forecasting models obtained for each energetic series, have a satisfactory degree of statistical validity (Low approximation errors) and are suitable for use as reference inputs in the Regional Energetic Plan of Asturias.
2
artículo
This project seeks to explore the phenomenon of earthquakes through the use of statistical tools, in this case to characterize and search for patterns of behavior of earthquakes, which have occurred in Peru in 2017; for this purpose, techniques such as Cluster Analysis and Time Series Models are used. First, the zones of greatest seismic activity have been identified and then their main characteristics have been found, as well as the interrelation between magnitude and depth. Apart from identifying the seismic zones, a small decreasing trend in the magnitude of earthquakes in Lima in the last three months has been observed. The data have been fitted to an ARIMA (1,1,0) time series model, which has been found to be significant, both at the national level and for Lima-Ica and Arequipa. Data from the Peruvian Geophysical Institute on its web page has been used. The most active area is the A...
3
artículo
Publicado 2021
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The objective was to build a time series forecast model based on endogenous patterns and variables of drinking water consumption and additionally determine the trend, seasonality, cyclical patterns and characteristics of the water consumed in the city of Tacna for the obtaining forecasts. The research was non-experimental, correlational and longitudinal, with monthly information from January 2006 to March 2018 recorded through documentary analysis. The unit of analysis were the economic units of the city of Tacna with drinking water service connected to the public network and monthly consumption as variable of interest. The population corresponds to a finite series of monthly data of size N = 383 months. The sample consisted of 139 observations between January 2006-July 2017 with which the ARIMA model has been built based on the Box-Jenkins methodology and extended until March 2018, for ...
4
artículo
Publicado 2021
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The objective was to build a time series forecast model based on endogenous patterns and variables of drinking water consumption and additionally determine the trend, seasonality, cyclical patterns and characteristics of the water consumed in the city of Tacna for the obtaining forecasts. The research was non-experimental, correlational and longitudinal, with monthly information from January 2006 to March 2018 recorded through documentary analysis. The unit of analysis were the economic units of the city of Tacna with drinking water service connected to the public network and monthly consumption as variable of interest. The population corresponds to a finite series of monthly data of size N = 383 months. The sample consisted of 139 observations between January 2006-July 2017 with which the ARIMA model has been built based on the Box-Jenkins methodology and extended until March 2018, for ...
5
artículo
Hybrid ANN-ARIMA models have been built by remodeling, to make the forecasts of the new cases of infections by Covid-19 in Peru, for this the confirmed cases of Covid-19 were extracted and used between the period 06/03/20 until 02/28/21, from the open data platform of the Ministry of Health. The results found indicate that the 02 best models correspond to the multiplicative hybrid model NNAR (27, 1, 6) * ARIMA (3, 0, 2) (1, 0, 1), and to the additive hybrid model NNAR (27, 1, 6) + ARIMA (1, 0, 1), whose values of the mean absolute percentage error (MAPE) differ by only 0.575%, thus providing almost the same forecasts. Considering the average of the MAPE values for the 03 best models of each modeling category, it has been determined that the NNAR-ARIMA hybrid models are better than the MLP-ARIMA hybrid models, that the NNAR + ARIMA additive hybrid models have a superiority of 1.20 % on th...
6
artículo
Publicado 2024
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The study analyzes the export competitiveness of Peruvian coffee in international markets using the ARIMA model to forecast export trends. The objective is to identify factors influencing the sector's profitability and sustainability. Time series of export volumes and prices were evaluated, revealing that the ARIMA model allows for accurate predictions of future trends. The results suggest that the Peruvian coffee sector faces challenges related to international price fluctuations and global competition. Emphasis is placed on the importance of efficiency in production and export processes to maintain and enhance the competitiveness of Peruvian coffee in the global market.
7
artículo
Publicado 2007
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El Niño connects globally climate, ecosystems and socio-economic activities. Since 1980 this event has been tried to be predicted, but until now the statistical and dynamical models are insuffi cient. Thus, the objective of the present work was to explore using an autoregressive moving average model the effect of El Niño over the sea surface temperature (TSM) off the Peruvian coast. The work involved 5 stages: identifi cation, estimation, diagnostic checking, forecasting and validation. Simple and partial autocorrelation functions (FAC and FACP) were used to identify and reformulate the orders of the model parameters, as well as Akaike information criterium (AIC) and Schwarz criterium (SC) for the selection of the best models during the diagnostic checking. Among the main results the models ARIMA(12,0,11) were proposed, which simulated monthly conditions in agreement with the observed ...
8
artículo
El análisis univariante de series temporales ARIMA (Autoregressive lntegrated Moving Average), basado en que una serie temporal obedece a un proceso estocástico, se ha utilizado para describir y predecir el comportamiento futuro de las series energéticas de mayor representatividad dentro la oferta y consumo de energía en el Principado de Asturias- España. En primer lugar, cada una de estas variables se han contabilizado mensualmente desde 1980 hasta 1996. De acuerdo a las características de cada serie - poseen tendencia, estacionalidad y el tamaño muestral suficiente - se procede a calcular qué modelo ARIMA univariante describe mejor a cada una de ellas. La aplicación de esta metodología consiste en calcular las predicciones de las principales variables energéticas de Asturias. Los resultados obtenidos han alcanzado un alto nivel de aproximación predictiva los cuales sirven c...
9
artículo
Publicado 2007
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El Niño connects globally climate, ecosystems and socio-economic activities. Since 1980 this event has been tried to be predicted, but until now the statistical and dynamical models are insuffi cient. Thus, the objective of the present work was to explore using an autoregressive moving average model the effect of El Niño over the sea surface temperature (TSM) off the Peruvian coast. The work involved 5 stages: identifi cation, estimation, diagnostic checking, forecasting and validation. Simple and partial autocorrelation functions (FAC and FACP) were used to identify and reformulate the orders of the model parameters, as well as Akaike information criterium (AIC) and Schwarz criterium (SC) for the selection of the best models during the diagnostic checking. Among the main results the models ARIMA(12,0,11) were proposed, which simulated monthly conditions in agreement with the observed ...
10
artículo
Publicado 2012
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The article reviews the concepts of prediction and presents a new methodology, which uses the Box- Jenkins class, for prediction of demand for calls, which make customers call centers known as callcenter. The study concludes that the use of time series tools, works efficiently, which would be in improving the efficiency and competitiveness in the call center.
11
artículo
The article reviews the concepts of prediction and presents a new methodology, which uses the Box- Jenkins class, for prediction of demand for calls, which make customers call centers known as callcenter. The study concludes that the use of time series tools, works efficiently, which would be in improving the efficiency and competitiveness in the call center.
12
tesis de grado
Publicado 2018
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This study is of descriptive observational longitudinal type, with tendency, having like main_x000D_ objective to determine a model of forecast that better explains the behavior of the monthly_x000D_ production of cacao, using information of the Central Bank of Reserve of Peru (BRCP) from the period January 2012 - July 2018, this being an applied investigation. The applied_x000D_ statistical methodology was the one proposed by Box-Jenkins and the series was divided_x000D_ into: january 2012 to july 2017 for the estimation of the model and from august 2017 to july 2018 for the validation of the forecast, this statistical technique is in charge of describing the characteristics of the series, in terms of its components of interest such as its trend and stationarity as well as predicting future values of the variable, the processing of them was carried out with the statistical program Eview...
13
tesis de grado
Publicado 2023
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The purpose of this research is to compare the ARIMA methodology and Recurrent _x000D_ Neural Networks to find the best model to forecast Inflation in Peru. The research consisted _x000D_ of a study sample from January 2000 to December 2021._x000D_ When designing the series model for each series, a forecast was made for all the _x000D_ months of the year 2022, which were compared with the real data to determine which _x000D_ methodology makes a better forecast. The results indicated that the previous LSTM recurrent _x000D_ neural network model obtained a lower forecast evaluation error compared to the ARIMA _x000D_ methodology, for which the RMSE, MAE, MAPE, EMC and MPE indicators were used
14
tesis de grado
Publicado 2011
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The prognosis models are by their same definition tools to quantify phenomena to develop methodologies for the decision making. Taking into account this situation the following problem considered: What is the forecast model and the quantity per package in domestic sales of the company Rubio SAC?_x000D_ By means of the prognosis models we can put financial and commercial phenomena in statistical terms, which allow to see the things us from the suitable perspective and low terms directly applied to the case, finally to make a decision that allows so much the economic efficiency as technical in the companies. Specifically, Models ARIMA will be the objective of this investigation. One says that models ARIMA reflect the behavior of a phenomenon through a certain period._x000D_ Coming to determine the forecasting model estimated for the series of the quantity per package sold by the company Ru...
15
artículo
Publicado 2014
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Para realizar las predicciones de series de tiempo uno de los métodos más usados es el método ARIMA, y consistió en determinar los modelos ARIMA de las precipitaciones mensuales, en las estaciones meteorológicas ubicadas en el Callejón de Huaylas: Yanacocha, Punta Mojón, Lampas Alto, Recreta, Cahuish, Querococha, Schacaypampa, Pachacoto, Ticapampa, Huancapetí, Huaraz, Chancos, Llanganuco, Parón y Caraz.Los modelos ARIMA de las precipitaciones mensuales se obtuvieron mediante el software Census X12 —ARIMA.Los modelos ARIMA de las precipitaciones mensuales son más variados que los modelos ARIMA de los caudales en el Callejón de Huaylas.
16
artículo
Publicado 2014
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Para realizar las predicciones de series de tiempo uno de los métodos más usados es el método ARIMA, y consistió en determinar los modelos ARIMA de las precipitaciones mensuales, en las estaciones meteorológicas ubicadas en el Callejón de Huaylas: Yanacocha, Punta Mojón, Lampas Alto, Recreta, Cahuish, Querococha, Schacaypampa, Pachacoto, Ticapampa, Huancapetí, Huaraz, Chancos, Llanganuco, Parón y Caraz.Los modelos ARIMA de las precipitaciones mensuales se obtuvieron mediante el software Census X12 —ARIMA.Los modelos ARIMA de las precipitaciones mensuales son más variados que los modelos ARIMA de los caudales en el Callejón de Huaylas.
17
artículo
Publicado 2014
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The daily electric demand in Peruvian National Interconnected System-SEIN- has very particular trend, seasonality and characteristics external effects, a situation that complicates the process of estimating the short-term forecast. The aim of this paper is to formulate and calculate ARIMA models with External Events Analysis to achieve efficient forecasts of electricity demand each day, at total level and broken down by areas of the SEIN. The methodology is based on treating each time series using appropriate statistical-mathematical transformations to achieve stability in variance as regular seasonal averages, parallel external events to try to reach an optimal predictive model ARIMA each area of the electrical system of Peru (Central, South and North) and for each day of the week. The results demonstrate the predictive efficiency. Taking as a quality indicator forecast the Mean Absolut...
18
tesis doctoral
Publicado 2024
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Este estudio se propuso “establecer el modelamiento de los parámetros meteorológicos que mediante inteligencia artificial contribuye significativamente en el clima en el Centro de Investigación del Estudio de la Actividad Solar y sus Efectos Sobre la Tierra, Ica, 2019-2022”. Estrategia metodológica adoptada siguió la estructura CRISP-DM y comprendió la preparación de datos, análisis de la temperatura, aplicación de modelos ARIMA y VAR para predicción meteorológica, y evaluación de la eficacia de los modelos. Resultados, destacaron la presencia de datos faltantes, cuya imputación fue esencial para mantener la integridad temporal del conjunto de datos. La aplicación de modelos ARIMA y VAR mostró que ARIMA superó en precisión a VAR en varias métricas de evaluación. Discusión, se centró en la importancia de abordar los datos faltantes y la necesidad de explorar model...
19
artículo
Publicado 2014
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The daily electric demand in Peruvian National Interconnected System-SEIN- has very particular trend, seasonality and characteristics external effects, a situation that complicates the process of estimating the short-term forecast. The aim of this paper is to formulate and calculate ARIMA models with External Events Analysis to achieve efficient forecasts of electricity demand each day, at total level and broken down by areas of the SEIN. The methodology is based on treating each time series using appropriate statistical-mathematical transformations to achieve stability in variance as regular seasonal averages, parallel external events to try to reach an optimal predictive model ARIMA each area of the electrical system of Peru (Central, South and North) and for each day of the week. The results demonstrate the predictive efficiency. Taking as a quality indicator forecast the Mean Absolut...
20
artículo
Publicado 2021
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El objetivo fue construir un modelo de pronóstico de series de tiempo en base a patrones y variables endógenas del consumo del agua potable y adicionalmente determinar la tendencia, estacionalidad, los patrones cíclicos y las características del agua que se consume en la ciudad de Tacna para la obtención de pronósticos. La investigación fue no experimental, correlacional y longitudinal, con información de periodicidad mensual entre enero de 2006 hasta marzo de 2018 registrada mediante análisis documental. La unidad de análisis fueron las unidades económicas de la ciudad de Tacna con servicio de agua potable conectado a la red pública y consumo mensual como variable de interés. La población corresponde a una serie finita de datos mensuales de tamaño N=383 meses. La muestra estuvo constituida por 139 observaciones entre enero 2006-julio 2017 con los que se ha construido el m...
