127 resultados para cost functions

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

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The threats caused by global warming motivate different stake holders to deal with and control them. This Master's thesis focuses on analyzing carbon trade permits in optimization framework. The studied model determines optimal emission and uncertainty levels which minimize the total cost. Research questions are formulated and answered by using different optimization tools. The model is developed and calibrated by using available consistent data in the area of carbon emission technology and control. Data and some basic modeling assumptions were extracted from reports and existing literatures. The data collected from the countries in the Kyoto treaty are used to estimate the cost functions. Theory and methods of constrained optimization are briefly presented. A two-level optimization problem (individual and between the parties) is analyzed by using several optimization methods. The combined cost optimization between the parties leads into multivariate model and calls for advanced techniques. Lagrangian, Sequential Quadratic Programming and Differential Evolution (DE) algorithm are referred to. The role of inherent measurement uncertainty in the monitoring of emissions is discussed. We briefly investigate an approach where emission uncertainty would be described in stochastic framework. MATLAB software has been used to provide visualizations including the relationship between decision variables and objective function values. Interpretations in the context of carbon trading were briefly presented. Suggestions for future work are given in stochastic modeling, emission trading and coupled analysis of energy prices and carbon permits.

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In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

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The aim of this master’s thesis was to document the present state and to create a development plan for Moventas Wind’s cost accounting. The current cost accounting system was evaluated and most fundamental problems were chosen as areas of focus in development work. The development plan includes both short- and long-term development proposals for problems identified. This report presents two alternative models for product costing. Benchmarking of cost accounting practices and modern cost accounting theories were used in development of cost accounting. It was found that the current cost accounting system functions quite well and the adjustments in unit cost rate calculation have only a minor influence on costs of goods sold. An OEE-based standard cycle concept was also developed and it was found that the implementation of this new system is worthwhile in the long-term.

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Electricity distribution network operation (NO) models are challenged as they are expected to continue to undergo changes during the coming decades in the fairly developed and regulated Nordic electricity market. Network asset managers are to adapt to competitive technoeconomical business models regarding the operation of increasingly intelligent distribution networks. Factors driving the changes for new business models within network operation include: increased investments in distributed automation (DA), regulative frameworks for annual profit limits and quality through outage cost, increasing end-customer demands, climatic changes and increasing use of data system tools, such as Distribution Management System (DMS). The doctoral thesis addresses the questions a) whether there exist conditions and qualifications for competitive markets within electricity distribution network operation and b) if so, identification of limitations and required business mechanisms. This doctoral thesis aims to provide an analytical business framework, primarily for electric utilities, for evaluation and development purposes of dedicated network operation models to meet future market dynamics within network operation. In the thesis, the generic build-up of a business model has been addressed through the use of the strategicbusiness hierarchy levels of mission, vision and strategy for definition of the strategic direction of the business followed by the planning, management and process execution levels of enterprisestrategy execution. Research questions within electricity distribution network operation are addressed at the specified hierarchy levels. The results of the research represent interdisciplinary findings in the areas of electrical engineering and production economics. The main scientific contributions include further development of the extended transaction cost economics (TCE) for government decisions within electricity networks and validation of the usability of the methodology for the electricity distribution industry. Moreover, DMS benefit evaluations in the thesis based on the outage cost calculations propose theoretical maximum benefits of DMS applications equalling roughly 25% of the annual outage costs and 10% of the respective operative costs in the case electric utility. Hence, the annual measurable theoretical benefits from the use of DMS applications are considerable. The theoretical results in the thesis are generally validated by surveys and questionnaires.

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Target company of this study is a large machinery company, which is, inter alia, engaged in energy and pulp engineering, procurement and construction management (EPCM) supply business. The main objective of this study was to develop cost estimation of the target company by providing more accurate, reliable and up-to-date information through enterprise resource planning (ERP) system. Another objective was to find cost-effective methods to collect total cost of ownership information to support more informed supplier selection decision making. This study is primarily action-oriented, but also constructive, and it can be divided in two sections: theoretical literature review and empirical study on the abovementioned part of the target company’s business. Development of information collection is, in addition to literature review, based on nearly 30 qualitative interviews of employees at various organizational units, functions and levels at the target company. At the core of development was to make initial data more accurate, reliable and available, a necessary prerequisite for informed use of the information. Certain development suggestions and paths were presented in order to regain confidence in ERP system as information source by reorganizing work breakdown structure and by complementing mere cost information with quantitative, technical and scope information. Several methods to use the information ever more effectively were also discussed. While implementation of the development suggestions outreached the scope of this study, it was forwarded in test environment and interest groups.

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The importance of industrial maintenance has been emphasized during the last decades; it is no longer a mere cost item, but one of the mainstays of business. Market conditions have worsened lately, investments in production assets have decreased, and at the same time competition has changed from taking place between companies to competition between networks. Companies have focused on their core functions and outsourced support services, like maintenance, above all to decrease costs. This new phenomenon has led to increasing formation of business networks. As a result, a growing need for new kinds of tools for managing these networks effectively has arisen. Maintenance costs are usually a notable part of the life-cycle costs of an item, and it is important to be able to plan the future maintenance operations for the strategic period of the company or for the whole life-cycle period of the item. This thesis introduces an itemlevel life-cycle model (LCM) for industrial maintenance networks. The term item is used as a common definition for a part, a component, a piece of equipment etc. The constructed LCM is a working tool for a maintenance network (consisting of customer companies that buy maintenance services and various supplier companies). Each network member is able to input their own cost and profit data related to the maintenance services of one item. As a result, the model calculates the net present values of maintenance costs and profits and presents them from the points of view of all the network members. The thesis indicates that previous LCMs for calculating maintenance costs have often been very case-specific, suitable only for the item in question, and they have also been constructed for the needs of a single company, without the network perspective. The developed LCM is a proper tool for the decision making of maintenance services in the network environment; it enables analysing the past and making scenarios for the future, and offers choices between alternative maintenance operations. The LCM is also suitable for small companies in building active networks to offer outsourcing services for large companies. The research introduces also a five-step constructing process for designing a life-cycle costing model in the network environment. This five-step designing process defines model components and structure throughout the iteration and exploitation of user feedback. The same method can be followed to develop other models. The thesis contributes to the literature of value and value elements of maintenance services. It examines the value of maintenance services from the perspective of different maintenance network members and presents established value element lists for the customer and the service provider. These value element lists enable making value visible in the maintenance operations of a networked business. The LCM added with value thinking promotes the notion of maintenance from a “cost maker” towards a “value creator”.

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Tässä insinöörityössä käsitellään Elisa OYJ:ssä käytössä olevia keskitettyjä IP-vaihdepalveluja. Työn tarkoituksena on tarkastella kolmen eri vaihdevalmistajan, Siemensin, Ciscon ja Centilen, keskitettyjä IP-vaihderatkaisuja. Työn tarkoituksena on myös tu-tustuttaa perinteisen puhelintekniikan parissa työskenteleviä ihmisiä VOIP-järjestelmiin. Työssä tarkastellaan yleisesti VOIPia henkilöasiakkaan, yritysasiakkaan ja laitevalmistajan näkökulmista, perehdytään IP-vaihteiden rakenteisiin ja palveluihin, käsitellään IP-vaihteiden hallintaa, viankorjausta ja valvontaa sekä käydään läpi IP-vaihteiden kustannuksellis - toiminnallinen vertailu. Yhteenvetona voidaan todeta, että tällä hetkellä perinteisien puhelinjärjestelmävalmistajien IP-vaihteet tarjoavat monipuolisemmat toiminnot kuin uusien vaihdevalmistajien IP-vaihteet.

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Selostus: Sian kasvuominaisuuksien perinnölliset tunnusluvut arvioituna kolmannen asteen polynomifunktion avulla

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Selostus: Kustannus-hyötyanalyysi monivaikutteisesta maataloudesta

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Abstract

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Tämä diplomityö käsittelee työkaluja, jotka on suunniteltu kustannusten ennakointiin ja hinnan asetantaan. Aluksi on käyty läpi perinteisen ja toimintoperusteisen kustannuslaskennan perusteita. Näiden menetelmien välisiä eroja on tarkasteltu ja toimintoperusteisen kustannuslaskennan paremmin sopivuus nykypäivän yrityksille on perusteltu. Toisena käsitellään hinnoittelu. Hinnan merkitys, hinnoittelumenetelmät ja päätös lopullisesta hinnasta on käyty läpi. Hinnoittelun jälkeen esitellään kustannusjärjestelmät ja kustannusten arviointi. Nämä asiat todistavat, että tarkat kustannusarviot ovat elintärkeitä yritykselle. Tuotteen kustannusarviointi, hinnan asetanta ja tarjoaminen ovat erittäin merkityksellisiä asioita ottaen huomioon koko projektin elinkaaren ja tulevat tuotot. Nykyään on yleistä käyttää työkaluja kustannusarvioinnissa ja joskus myös hinnoittelussa. Työkalujen luotettavuus on tiedettävä, ennenkuin työkalut otetaan käyttöön. Myös työkalujen käyttäjät täytyy perehdyttää hyvin. Muuten yritys todennäköisesti kohtaa odottamattomia ja epämiellyttäviä yllätyksiä.

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Diplomityöntavoitteena on tutkia, kuinka nimiketiedon hallinnalla voidaan parantaa kustannustehokkuutta projektiohjautuvassa toimitusketjussa. Työn kohdeyritys on Konecranes Oyj:n tytäryhtiö Konecranes Heavy Lifting Oy. Nimiketiedon hallinta liittyy läheisesti tuotetiedon hallintaan. Teoriaosassa käsitellään toimitusketjuympäristön tekijöitä, modulaarisuuden ja asiakaskohtaisuuden ongelmallisuutta sekä informaatiovirran vaikutuksia eri toiminnoissa. Yritysosassa vertaillaan konsernitason kahta liiketoiminta-aluetta strategiavalintojen, tuotteiden modulaarisuuden sekä tilaus-toimitusprosessissa liikkuvan nimikeinformaation perusteella. Diplomityön tuloksena annetaan suuntaviivat; nimikemassan eheytykseen, strategisten nimikkeiden tunnistamiseen ja määrittämiseen, nimikkeiden hallintaan sekä master-datan sijoittamiseen tietojärjestelmäympäristöön.