• Asia pacific journal of information systems
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• 제7권1호
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• pp.67-83
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• 1997

The utility of learning techniques in investment analysis has been demonstrated in many areas, ranging from forecasting individual stocks to entire market indexes. To date, however, the application of artificial intelligence to financial forecasting has focused largely on short predictive horizons. Usually the forecast window is a single period ahead; if the input data involve daily observations, the forecast is for one day ahead; if monthly observations, then a month ahead; and so on. Thus far little work has been conducted on the efficacy of long-term prediction involving multiperiod forecasting. This paper examines the impact of alternative procedures for extended prediction using knowledge discovery techniques. One dimension in the study involves temporal granularity: a single jump from the present period to the end of the forecast window versus a web of short-term forecasts involving a sequence of single-period predictions. Another parameter relates to the numerosity of input variables: a technical approach involving only lagged observations of the target variable versus a fundamental approach involving multiple variables. The dual possibilities along each of the granularity and numerosity dimensions entail a total of 4 models. These models are first evaluated using neural networks, then compared against a multi-input jump model using case based reasoning. The computational models are examined in the context of forecasting the S&P 500 index.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1505-1509
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• 2005

This paper introduces a new architecture of genetically optimized self-organizing fuzzy polynomial neural networks by means of information granulation. The conventional SOFPNNs developed so far are based on mechanisms of self-organization and evolutionary optimization. The augmented genetically optimized SOFPNN using Information Granulation (namely IG_gSOFPNN) results in a structurally and parametrically optimized model and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNN. With the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The GA-based design procedure being applied at each layer of genetically optimized self-organizing fuzzy polynomial neural networks leads to the selection of preferred nodes with specific local characteristics (such as the number of input variables, the order of the polynomial, a collection of the specific subset of input variables, and the number of membership function) available within the network. To evaluate the performance of the IG_gSOFPNN, the model is experimented with using gas furnace process data. A comparative analysis shows that the proposed IG_gSOFPNN is model with higher accuracy as well as more superb predictive capability than intelligent models presented previously.

• 여성건강간호학회지
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• 제21권4호
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• pp.308-320
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• 2015

Purpose: The aim of this study was to determine the predictive factors for maternal role development for mothers of premature infants. Methods: A descriptive correlational study was conducted. A total sample of 121 mothers of premature infants following discharge from the neonatal intensive care unit were recruited using two strategies; an internet-based survey and an in-person data collection in a tertiary university hospital in Korea. A self-report questionnaire was used to collect data regarding personal, birth variables, marital intimacy, maternal attachment, maternal identity and maternal role development. Results: A hierarchical multiple regression analysis indicated that parity, maternal attachment, marital intimacy and maternal identity were predictors for maternal role development for mothers of premature infants, accounting for 70% of the variance. Among these variables, maternal attachment is the most powerful predictor for maternal role development. Conclusion: Nursing interventions during hospitalization to post-discharge education that includes parents of premature babies with positive interaction between couples strengthening marital intimacy and promotes maternal attachment that leads to integrate maternal identity should be considered by priority. Community-based family services such as home visits should be focused on maximizing the predictive factors for maternal role development in transition to motherhood that can contribute to maternal health as well as optimal growth and development of premature infants.

• 한국도로학회논문집
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• 제14권5호
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• pp.189-199
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• 2012

PURPOSES: The purpose of this study is to propose a new methodology for developing statistical collision models and to show the validation results of the methodology. METHODS: A new modeling method of introducing variables into the model one by one in a multiplicative form is suggested. A method for choosing explanatory variables to be introduced into the model is explained. A method for determining functional forms for each explanatory variable is introduced as well as a parameter estimating procedure. A model selection method is also dealt with. Finally, the validation results is provided to demonstrate the efficacy of the final models developed using the method suggested in this study. RESULTS: According to the results of the validation for the total and injury collisions, the predictive powers of the models developed using the method suggested in this study were better than those of generalized linear models for the same data. CONCLUSIONS: Using the methodology suggested in this study, we could develop better statistical collision models having better predictive powers. This was because the methodology enabled us to find the relationships between dependant variable and each explanatory variable individually and to find the functional forms for the relationships which can be more likely non-linear.

• 성인간호학회지
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• 제27권6호
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• pp.613-623
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• 2015

Purpose: This study was designed to construct a predictive model to explain quality of life of stomach cancer patients with gastrectomy. Methods: Data were collected from July 10 to August 30, 2013 through survey using self-reported questionnaires. A total of 218 patients with gastrectomy was recruited from three different hospitals. Outcome variables were exogenous ones (self efficacy and social support) and endogenous ones (depression, perceived health status, self care behavior, and quality of life). Results: Goodness-of-fit of the hypothetical model was $x^2=143.37$, RMSEA=.07 CFI=.95, TLI=.93 SRMR=.05. Self care behavior, depression and perceived health status had significant direct effects on quality of life. Self efficacy and social support were affected quality of life indirectly. These variables explained 67.9% of total variance of quality of life, and self-care behavior was the most influential factor for quality of life. Conclusion: The findings of this study suggested that self care behavior must be considered as an intervention strategy to improve quality of life. Also a development of a specific intervention program to promote self efficacy and control depression for patients with gastrectomy is essential to facilitate their self care behaviors.

• 환경영향평가
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• 제20권5호
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• pp.663-673
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• 2011

In the face of accelerating biodiversity loss and its significance in our coexistence with nature, biodiversity is becoming more crucial in sustainable development perspective. To estimate biodiversity in the future which provides valuable information for decision making system especially in the national level, a quantitative approach must be studied forehand as a baseline of the present status. In this study, we developed a large-scale map of Plant Species Richness (PSR, typical indicator of biodiversity) for Young-dong and Pyung-chang provinces. Due to the accessibility of appropriate data and advance of modelling techniques, reduction of variables without deteriorating the predictive power is considered by applying Genetic algorithm. In addition, a number of Correctly Classified Instances (CCI) with 10-fold cross validation which indicates the predictive power, was carried out for evaluation. This study, as a fundamental baseline, will be beneficial in future land work as well as ecosystem restoration business or other relevant decision making agenda.

• 대한토목학회논문집
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• 제38권6호
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• pp.801-808
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• 2018

선형회귀모형의 학습은 일반적으로 자료의 개수가 설명변수의 개수보다 충분히 크고, 설명변수들 사이에 심각한 다중공선성이 없다는 가정 하에서 안정적으로 이루어진다. 본 연구에서는 이러한 가정이 위배되었을 경우 모형 학습의 어려움을 실제 호우피해자료를 분석함으로써 조명하였고, 이를 해결하기 위해 자료를 통합한 다음 주성분회귀모형 또는 능형회귀모형을 사용할 것을 검토하였다. 모형의 학습에 사용된 자료와 별도의 독립된 자료에서 제안된 모형들의 예측력을 평가하였고, 제안된 방법이 선형회귀모형보다 더 나은 예측력을 보이는 것을 확인하였다.

• 대한의생명과학회지
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• 제25권3호
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• pp.256-266
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• 2019

In this study, obese adults were compared for their ability to predict obesity and lipid related variables and their optimal cutoff values to predict metabolic syndrome and insulin resistance. In this study, 9,256 adults aged 20 years or older and less than 80 years old, who were in the Gyeonggi region from January 2014 to December 2016 and who were examined at a general hospital, were enrolled. The diagnostic criteria for obesity were WHO (World Health Organization), and BMI $25kg/m^2$ or more presented in the Asia-Pacific region. Metabolic syndrome was diagnosed based on the criteria of American Heart Association / National Heart, Lung, and Blood Institute (AHA / NHLBI). According to the results of receiver operating characteristic curve (ROC) analysis, Triglyceride / HDL-cholesterol (TG / HDL-C), Triglyceride and Glucose (TyG) index, lipid accumulation product (LAP) and visceral adiposity index (VAI) showed high predictive power for diagnosing metabolic syndrome. The diagnostic accuracy of LAP (AUC: 0.854) for males and VAI (0.888) for females was the highest. The optimal cutoff value of LAP was 42.71 for male and 35.44 for female, and the cutoff value of VAI was 1.92 for male and 2.15 for female. In addition, WHtR (waist to height ratio), TyG index, and LAP were used as predictors of insulin resistance in obese adults. Therefore, LAP and VAI were superior to other indicators in predicting metabolic syndrome in obese adults.

• 응용통계연구
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• 제34권4호
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• pp.623-632
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• 2021

본 연구에서는 여러가지 시계열 모형 중 평활법(가법계절지수, 승법계절지수), 계절 ARIMA 모형, ARARCH 그리고 AR-GARCH 회귀모형을 이용하여 최대 전력수요를 예측하는 방법을 연구하였다. 이 때 가중 평균모형으로 추세를 갖는 시계열 모형과 온도에 대한 회귀 모형을 적절한 가중치로 예측 정확도를 높이는 방법도 연구하였다. 결과적으로 AR-GARCH 회귀모형으로 예측하는 것이 가중 우수함을 보였다.

• 대한가정학회지
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• 제29권2호
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• pp.199-215
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• 1991

The purpose of the study is to investigate the relation between marital communication types and self-esteem demographic-socioligical variables to eliminate the methodlogical contradiction of previous studies, this study aimed as follows: (1) correlation between marital communication types and all the independent variables, such as self-esteem, sex, age, academic history, mate selection type, family type, duration of marriage, religion, etc. and marital communication types. (2) discriminating powers of marital communication types by way of the variables mentioned above. In this study questionaire was used on 392 married Seoulites, which consists of two scales and 9 items. In order to verify the hypotheses, the following two methods were used: (1) LOGIT program to the correlation between norminal scale and /or interval scale. (2) discriminating analysis of marital communication types by way of the variables. The results of the study are as follows: (1) Only 4 variables, such as self-esteem, sex, duration of marriage and academic history, correlate with marital communication types in level P<0.05 (2) According to the discriminating analysis of the variables mentioned above, marital communication types cannot be predicted as the predictive power is only 32.2%. (3) Correlation coefficent of authoritic communication type is higher males than females and higher low degree group of self-esteem than high degree group. (4) In the some communication types, direction of correlation coefficent is different in the some variables.