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Earned Value Analysis (EVA) is a well- known planning and control management system that integrates cost, schedule and technical performance. It allows for the calculation of cost and schedule variances, and performance indices as well as forecasting project final cost and schedule duration. The Earned Value Analysis method provides timely assessment of project performance highlighting the need for eventual corrective action. Earned Value Analysis method (EVA) was originally developed for cost management and has not been widely used for forecasting project duration. EVA typically calculate the Schedule Efficiency through the Schedule Performance Index (SPI) based on budgeted cost and not on the time of work(s) accomplished. Therefore, it may not accurately determine the time - base schedule efficiency, particularly for late completion projects, and it makes it difficult to correlate the final duration with project planned duration determined through critical path network (CPM) calculation. The purpose of this study is to compare the classic Earned Value Performance Indicators with the time dependent Earned Schedule Performance Indicators to help a program manager(s) to estimate / predict a more realistic /reliable time duration of project that can better correlate with CPM. It also explores how Building Information Modeling (BIM) tools simulation could be incorporated with Base-line or S-curve to reflect the timely phased physical progress synthesis during the development of project as opposed to the traditional use of cash flow analysis.

Neural Networks

This research project examines the link between social media and its effect on stock exchanges and movement of stocks. The study uses Twitter as its primary social media platform and focuses on its effect on the Johannesburg Stock Exchange. The study examines various forms of social media and micro-blogging sites in its attempt to provide a thorough understanding of the role of social media within the market. In line with its exploration of social media, the study analyses User-Generated Content, Sentiment Analysis and the impact of Word-of-Mouth. A brief explanation of Algorithmic Trading, the Efficient Market Hypothesis, and the Adaptive Market Hypothesis is also provided. The information used to show the relationship between Twitter and the JSE was extracted using a quantitative survey answered by registered traders on the JSE. The survey aimed to ascertain the level of information pertaining to stock movement posted to the platform by these traders, and how these traders used that same information to make trading decisions. The results of the study show that Twitter and other micro-blogging sites have a level of determination in stock exchanges. This study shows that traders make some use of online information to inform their trading decisions on the Stock Market. The validity of this online information stems from the fact that traders place trust in other people and other users’ experience, as proven by Word of Mouth. The findings of this study were contrary to the researchers’ expectation that Twitter was widely used as an informant for trade decisions. What is deduced from the available findings is that while Twitter and other social media platforms do to some extent provide information for traders on the JSE in making trade decisions, it is not a wide-spread basis for movement of shares. / Dissertation (MBA)--University of Pretoria, 2013. / zkgibs2014 / Gordon Institute of Business Science (GIBS) / MBA / Unrestricted

This research was designed to develop and evaluate an automated alternative to the Box-Jenkins method of forecasting. The study involved two major phases. The first phase was the formulation of an automated ARIMA method; the second was the combination of forecasts from the automated ARIMA with forecasts from two other automated methods, the Holt-Winters method and the Stepwise Autoregressive method. The development of the automated ARIMA, based on a decision criterion suggested by Akaike, borrows heavily from the work of Ang, Chuaa and Fatema. Seasonality and small data set handling were some of the modifications made to the original method to make it suitable for use with a broad range of time series. Forecasts were combined by means of both the simple average and a weighted averaging scheme. Empirical and generated data were employed to perform the forecasting evaluation. The 111 sets of empirical data came from the M-Competition. The twenty-one sets of generated data arose from ARIMA models that Box, Taio and Pack analyzed using the Box-Jenkins method. To compare the forecasting abilities of the Box-Jenkins and the automated ARIMA alone and in combination with the other two methods, two accuracy measures were used. These measures, which are free of magnitude bias, are the mean absolute percentage error (MAPE) and the median absolute percentage error (Md APE).

La maîtrise de la qualité est aujourd’hui indispensable pour satisfaire les exigences des clients. Bien qu’il existe différentes méthodes et outils spécialement développés pour manager la qualité des systèmes ou des processus au sein des entreprises, il est difficile d’établir le lien entre la maîtrise des nombreux processus d’une entreprise et la qualité produit pour un système en service. Dans ce contexte, une thèse CIFRE a été menée au sein de MBDA, entreprise qui conçoit, développe et produit des systèmes d’armes. La problématique de cette thèse est de développer une méthodologie permettant de produire une définition de la qualité produit d’un système complexe qui soit valable tout au long de son cycle de vie, et permettant la construction de modèles de prévision de la qualité produit en utilisation lors du développement et de la production. Notre contribution consiste en une méthodologie en deux phases. La première phase permet d’établir une définition de la qualité produit des systèmes complexes du point de vue du client adaptée au contexte industriel en définissant plusieurs facteurs qualité produit qui soit valable pour toutes les phases du cycle de vie des systèmes. La deuxième phase permet de construire des modèles de prévision de la qualité produit qui permettent d’obtenir une évaluation de la qualité tout au long du cycle de vie des systèmes et d’établir une prévision de ce que sera la qualité en utilisation. Les deux phases de la méthodologie reposent sur l’exploitation d’avis d’experts afin de permettre son utilisation sans disposer d’une quantité importante de données. Les modèles construits ont été testés pour des systèmes développés par MBDA. / Today, quality control is essential to satisfy customer requirements. Although there are different methods and tools specially developed to manage the quality of systems or processes within companies, it is difficult to establish the link between management of a company's many processes and product quality for a system in service. In this context, a CIFRE thesis was conducted within MBDA, a company that designs, develops and produces weapons systems. The problem of this thesis is to develop a methodology allowing to produce a definition of the product quality of a complex system which is valid throughout its life cycle, and allowing the construction of models to predict the product quality in use during development and production. Our contribution consists of a two-phase methodology. The first phase makes it possible to establish a definition of the product quality of complex systems from the customer's point of view adapted to the industrial context by defining several product quality factors that are relevant for all phases of the systems life cycle. The second phase builds product quality prediction models that provide a life-cycle quality assessment of the systems and a forecast of what the quality will be in use. Both phases of the methodology rely on the use of experts' judgement to enable its use without a significant amount of data. The models built have been tested for systems developed by MBDA.

The Inland Empire -Riverside and San Bernardino Counties - was one of the hardest hit areas in all of the United States during the Great Recession. Home prices have declined over 50%, significantly more than the 25% decline in the surrounding Los Angeles County, and housing starts have declined to over 90% from 2005. The Inland Empire has one of the highest unemployment rates in the US at 14.8%. This paper attempts to forecast the recovery for the Inland Empire. Employing univariate forecasts along with VAR(12) forecasts, focusing on housing starts and unemployment rates as the underlying variables, we find that there is little hope for a recovery over the next 3 years. The model predicts unemployment to either rise even more or, at best, remain stagnant. Housing starts are predicted to remain constant over the next three years.

圖書出版產業的競爭態勢激烈，是由來已久的問題，就以實際的數據顯示，2004年申請登錄ISBN的新書，種類就高達39713種，可是能在像是金石堂這樣的連鎖書店販售的新書，卻只有23195種；同時，在這二萬多本的新書中，能夠獲得消費者認同與購買的書更是少之又少。就是在這樣的環境中，圖書出版產業該如何生存，成為一個很重要的課題。 圖書出版其實就是藉由文字傳遞作者想要表達的情報，藉以創造利潤的產業。因此，穩定持續比快速週轉重要；要能穩定推出有品質且保障銷售的圖書，例如長銷書以及暢銷書，並建立健全完善的商品規劃與行銷方式，出版社才能有生存的機會與空間。現今出版產業分工清楚，從發行、編輯、業務、行銷、以及印刷管理各功能，都是獨立運作，可是創造出銷售良好的暢銷書，是必須從整體的觀點去審視，透過彼此合作與整合，降低資源浪費或是閒置的問題，產生最大的效益。本研究即以價值鏈各部份做為討論基礎，藉由調查出版從業人員，將市場暢銷書的成功特徵，加以歸納成為成功模式，試圖說明與預測暢銷書所需具備的要件。 圖書產業之價值流程，主要分為「市場資訊蒐集」、「圖書編輯與設計」、「圖書印刷」、「圖書宣傳與發行」、「圖書儲存銷售」、「圖書售後服務」，其各項目都包含了許多項目與因素。藉由因素分析，將價值鏈中『市場資訊收集』歸納出「作者創造需求」與「迎合社會議題」二因素；『文字編輯與設計』則有「內頁呈現與設計」、「書籍內文」、以及「書名與封皮」三因素；『圖書宣傳與設計』是「行銷手法運用」、「市場曝光度」以及「擁有通路力量」。在獲得因素選項後，帶入區別分析與邏輯迴歸模式中，進一步分析何者能成為解釋暢銷書成功之影響因子。 以不分類書種而言，「書名與封皮」、「行銷手法運用」與「市場曝光度」是最後萃取出的重要價值活動，這是導因於目前出版書種過於氾濫，為了讓書籍增加銷售率，出版業者必須讓消費者第一眼就能對書籍有好感，並且配合各樣的行銷方式，利用活動(如：參與書展、研討會等)與廣告，增加書籍在消費者的曝光率，成為市場之暢銷書機會就大增。一般而言，文學類書籍應該是會著重在「書籍內文」，分析結果卻應著重在「行銷手法的運用」，說明消費者對內文接受度已廣泛，如何把書的特性與魅力告訴消費者，才是文學類書籍的銷售的重要條件。受限於財經企管類書籍專業性程度不一，導致進入可能會有障礙。因此，成功之財經企管暢銷書籍，要能在「書名與封皮」給予很親近消費者之名稱，並透過「廣告」與相關議題「活動」之舉辦，向讀者介紹該本書之內容與實用性，增加購買意願。

Magistro baigiamajame darbe išanalizuota ir įvertinta tarptautinė valiutų rinka, jos struktūra bei analizės ir prognozės būdai. Taip pat analizuojami neuronini tinklai bei įvairios jų struktūros: daugiasluoksnis perseptronas, radialinių bazinių funkcijų neuroniniai tinklai, GRNN bei rekurentiniai neuroniniai tinklai. Tyrimu siekiama nustatyti ar valiutų kursų prognozavimo tikslumas, taikant neuroninius tinklus, priklauso nuo investavimo rizikos lygio. Darbas susideda iš trijų skyrių. Pirmame skyriuje nagrinėjama tarptautinės valiutų rinkos teorija, didesnį dėmesį atkreipiant į pačia FOREX koncepciją, rinkos dalyvius bei jų elgesį ir finansinius instrumentus, naudojamus šioje rinkoje. Tiriami pagrindiniai valiutų kursų prognozės bei analizės būdai, skirstant juos fundamentalią ir techninę analizę. Analizė atliekama, tiriant Lietuvos ir užsienio mokslininkų darbus valiutų rinkos prognozavimo srityje. Antrame skyriuje analizuojami neuroniniai tinklai. Aprašoma neuroninių tinklų koncepcija bei taikymo sritys. Naudojant literatūros analizės metodą, tiriami Lietuvos ir užsienio autorių moksliniai darbai, kuriuose aprašomi neuroninių tinklų tyrimai valiutų rinkos prognozavimo srityje. Pateikiama aktualiausių straipsnių meta analizė. Trečiame skyriuje atliekamas tyrimas su pasirinktų tyrimų duomenimis. Aprašomi šių pasirinkimo motyvai. Skyriaus galia pateikti statistiniai analizės rezultatai: MAE (angl. Mean absoliute error), MAPE (angl. Mean absolute percentage error) krypties... [toliau žr. visą tekstą] / The master thesis analyses the application of the neural networks for foreign exchange market forecast. Multilayer perceptron, radial basis functionneural networks, GRNN and recurrent neural networks are analyzed in order to find the correlation level between the forecast accuracy and the level of the investment risk. The work consists of three main parts. The first part analyses the conception, the main participants, trading characteristics and trading instruments of the FOREX market as well as the trading strategies and the methods of forecasting currency market. The second part is appointed to analyze the neural networks. The analyzes the conception, the structure and the application of the neural networks is made. The Meta-analyses of the main scientific articles are provided in every sub-part. In the third part the forecasting data analysis is performed to evaluate the correlation rate between the forecast accuracy and the level of the investment risk. Mean absolute error, Mean absolute percentage error, sign function andStandard deviation are used as indicators.