Modelling the colour difference by artificial neural network

This thesis work studies the modelling of the colour difference using artificial neural network. Multilayer percepton (MLP) network is proposed to model CIEDE2000 colour difference formula. MLP is applied to classify colour points in CIE xy chromaticity diagram. In this context, the evaluation was performed using Munsell colour data and MacAdam colour discrimination ellipses. Moreover, in CIE xy chromaticity diagram just noticeable differences (JND) of MacAdam ellipses centres are computed by CIEDE2000, to compare JND of CIEDE2000 and MacAdam ellipses. CIEDE2000 changes the orientation of blue areas in CIE xy chromaticity diagram toward neutral areas, but on the whole it does not totally agree with the MacAdam ellipses. The proposed MLP for both modelling CIEDE2000 and classifying colour points showed good accuracy and achieved acceptable results.

Forecasting of wind speeds and directions with artificial neural networks

In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.

Transparent Network Interfaces to Mobile Peer-to-Peer Environment

The fact that most of new Personal Data Assistant (PDA) devices and smartphones have the ability to communicate via different wireless technologies has made several new applications possible. While traditional network model is based on the idea of static hosts, mobile devices can create decentralized, self-organizing ad-hoc networks and act as peers in the network. This kind of adapting network is suitable for mobile devices which can freely join and leave the networks. Because several different wireless communication technologies are involved, flexible changing of the networking technology must be handled in order to enable seamless communication between these networks. This thesis presents a transparent network interface to mobile Peer-to-Peer environment which is named as Virtual PeerHood. Different wireless technologies and aspects of providing a seamless connectivity between these technologies are explored. The result is a middleware platform for mobile Peer-to-Peer environment, capable of handling several networking technologies.

Local Services in a Fourth Generation Mobile Network

Neljännen sukupolven mobiiliverkot kokoaa kaikki tietoliikenneverkot ja palvelut Internetin ympärille. Tämä mullistus muuttaa vanhat vertikaaliset tietoliikenneverkot joissa yhden tietoliikenneverkon palvelut ovat saatavissa vain kyseisen verkon päätelaitteille horisontaaliseksi malliksi jossa päätelaitteet käyttävät omaa verkkoansa pääsynä Internetin palveluihin. Tämä diplomityö esittelee idean paikallisista palveluista neljännen sukupolven mobiiliverkossa. Neljännen sukupolven mobiiliverkko yhdistää perinteiset televerkkojen palvelut ja Internet palvelut sekä mahdollistaa uuden tyyppisten palveluiden luonnin. TCP/IP protokollien ja Internetin evoluutio on esitelty. Laajakaistaiset, lyhyen kantaman radiotekniikat joita käytetään langattomana yhteytenä Internetiin on käsitelty. Evoluutio kohti neljännen sukupolven mobiiliverkkoja on kuvattu esittelemällä vanhat, nykyiset ja tulevat mobiiliverkot sekä niiden palvelut. Ennustukset palveluiden ja markkinoiden tulevaisuuden kehityksestä on käsitelty. Neljännen sukupolven mobiiliverkon arkkitehtuuri mahdollistaa paikalliset palvelut jotka ovat saatavilla vain yhdessä paikallisessa 4G verkossa. Paikalliset palvelut voidaan muunnella jokaiselle käyttäjälle erikseen käyttäen profiili-informaatiota ja paikkatietoa. Työssä on pohdittu paikallisten palveluiden käyttökelpoisuutta ja mahdollisuuksia käyttäen Lappeenrannan teknillisen korkeakoulun 4G projektin palvelupilotin tuloksia.

Phase voltage control and filtering in a converter-fed single-phase customer-end system of the LVDC distribution network

In recent years, the network vulnerability to natural hazards has been noticed. Moreover, operating on the limits of the network transmission capabilities have resulted in major outages during the past decade. One of the reasons for operating on these limits is that the network has become outdated. Therefore, new technical solutions are studied that could provide more reliable and more energy efficient power distributionand also a better profitability for the network owner. It is the development and price of power electronics that have made the DC distribution an attractive alternative again. In this doctoral thesis, one type of a low-voltage DC distribution system is investigated. Morespecifically, it is studied which current technological solutions, used at the customer-end, could provide better power quality for the customer when compared with the current system. To study the effect of a DC network on the customer-end power quality, a bipolar DC network model is derived. The model can also be used to identify the supply parameters when the V/kW ratio is approximately known. Although the model provides knowledge of the average behavior, it is shown that the instantaneous DC voltage ripple should be limited. The guidelines to choose an appropriate capacitance value for the capacitor located at the input DC terminals of the customer-end are given. Also the structure of the customer-end is considered. A comparison between the most common solutions is made based on their cost, energy efficiency, and reliability. In the comparison, special attention is paid to the passive filtering solutions since the filter is considered a crucial element when the lifetime expenses are determined. It is found out that the filter topology most commonly used today, namely the LC filter, does not provide economical advantage over the hybrid filter structure. Finally, some of the typical control system solutions are introduced and their shortcomings are presented. As a solution to the customer-end voltage regulation problem, an observer-based control scheme is proposed. It is shown how different control system structures affect the performance. The performance meeting the requirements is achieved by using only one output measurement, when operating in a rigid network. Similar performance can be achieved in a weak grid by DC voltage measurement. An additional improvement can be achieved when an adaptive gain scheduling-based control is introduced. As a conclusion, the final power quality is determined by a sum of various factors, and the thesis provides the guidelines for designing the system that improves the power quality experienced by the customer.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Modeling a Network of Heat Exchangers

This research work addresses the problem of building a mathematical model for the given system of heat exchangers and to determine the temperatures, pressures and velocities at the intermediate positions. Such model could be used in nding an optimal design for such a superstructure. To limit the size and computing time a reduced network model was used. The method can be generalized to larger network structures. A mathematical model which includes a system of non-linear equations has been built and solved according to the Newton-Raphson algorithm. The results obtained by the proposed mathematical model were compared with the results obtained by the Paterson approximation and Chen's Approximation. Results of this research work in collaboration with a current ongoing research at the department will optimize the valve positions and hence, minimize the pumping cost and maximize the heat transfer of the system of heat exchangers.

The transforming network of a foreign company operating in Mongolia. Case: A Finnish firm in Mongolia

In the globalising business environment ever fewer market areas remain unknown. Mongolia is yet only considered as an isolated strip between two power states. The purpose of this study is to put Mongolia on the map of academic business research. This is done by describing the transforming network of a foreign company operating in Mongolia. The objective of the study is approached through a case study, which presents the transformation of a Finnish company operating in Mongolia. This study aims at providing understanding on how the foreign case company observes the transformations of its network. The transformation within the case company is reflected to the transformations that occur in the Mongolian business environment. This study was conducted through a qualitative, intrinsic case study approach. The empirical data was gathered by using the method of network pictures. The network pictures were completed with the assistance of themed interviews. In order to be able to analyse the transformation within a network, three different time periods were observed: the past period around 2000, the present around 2014, and the estimated future around 2020. The data was collected from four executives positioned either in Finland, Russia or Mongolia. The respondents have a long experience within the case company, they hold managerial position, and therefore were able to offer valuable data for this study. The analytical framework used to analyse the collected data was built on the industrial network model, the ARA (actors-resources-activities)-model. The study shows that the changing business environment of Mongolia was utilised by the case company. In order to better meet the transforming customer wishes, the case company transformed from being a retailer to being a manufacturer. The case company was able to become a pioneer in the market. Thus, the case company has undergone similar kind of rapid transformation as the economy of Mongolia in entirety. This study shows that the general nature of the ARA-model makes it usable for new research contexts. The initial ARA-model offers a way to identify the dimensions of a network and a mean to understand these dimensions. The ARA-model can be applied to different contexts and to all time dimensions, past, present and future. The managerial recommendations offered in this study are directed towards the managers that plan to start operations in Mongolia. While this study is the first of its kind, it offers a good starting point for the future research on the change of Mongolian business networks. Valuable information could, for example, be obtained from a comparative study between the case company of this study and a multinational mining company operating in Mongolia.

Pienvesivoimalanmallinnus ja jakeluverkkovaikutusten tarkastelu

Tässä työssä simuloitiin Valkealassa sijaitsevaa Tirvan pienvesivoimalaitosta ja sen vaikutusta sähkönjakeluverkkoon. Pienvesivoimalaitos mallinnettiin PSCAD-ympäristöön verkko- ja voimalaitostietojen perusteella. Sähköverkko kuvattiin malliin koko 110 kV:n siirtävän verkon ja Tirvan pienjänniteverkon väliltä. Mallin avulla tehtiin sarja hajautettua sähköntuotantoa koskevia tarkasteluita. Tarkasteluissa huomattiin voimalaitoksen verkkoonliitynnän aiheuttavan standardien ylärajoilla olevan transienttisen muutoksen voimalaitoksen jännitteisiin. Työssä tehtiin yksityiskohtaisempi jännitehäviöiden mittaus voimalaitoksen pullonkaulana toimivalle pienitehoiselle jakelumuuntajalle. Tuotannon lisäämisen yhteydessä näkyvän yllättävän jännitteen laskun syyt paikannettiin muuntajalla tapahtuviin loistehon siirrosta johtuviin ylimääräisiin jännitehäviöihin. Voimalaitoksella ei ole merkittävää vaikutusta vikatilanteiden virtoihin.

Kestomagneettitahtikoneen lämpömallinnus

Sähkökoneenterminen suunnittelu on yhtä tärkeätä kuin koneen sähköisten piirien ja magneettipiirin mitoitus, koska koneen lämpenemä määrää koneesta saatavan tehon. Pääosasähkökoneista suunnitellaan edelleen ns. perimätiedon avulla, jossa tukeudutaanvalmiiksi koeteltuihin ratkaisuihin ja kokemusperäiseen tietoon tiettyjen rakenteiden toimivuudesta. Perinteisin menetelmin uusia konerakenteita suunniteltaessa ei pystytä saamaan luotettavaa tietoa uusien ratkaisuiden toimivuudesta. Etenkin hitaasti pyörivien ja suuren vääntötiheyden omaavien kestomagneettitahtikoneiden jäähdytyksen mitoitus on ongelmallista. Siten tarve kehittää analyyttisiä työkaluja lämpenemän mallinnukseen on perusteltua. Tässä työssäperehdytään suuren tehotiheyden omaavien kestomagneettikoneiden urakoon ja virrantiheyden valintaan termisen mitoituksen kannalta. Työn tavoitteena on laatia yksinkertainen analyyttinen työkalu urakoon ja virrantiheyden valintaan. Työkaluavoidaan hyödyntää jo koneensuunnittelun alkuvaiheessa.

Kolmannen sukupolven matkaviestinverkon puhelunohjaus MSC Server –konseptilla

Tietoliikenneala elää muutosten aikaa. Vanhat piirikytketyt kapeakaistaiset verkot ovat väistymässä seuraavan sukupolven verkkojen tieltä. GPRS-verkot tekevät tuloaan ja 3G-verkkojen kehitystyö on kiivaimmillaan laitetoimittajien ratkoessa verkoille asetettuja haasteita. Jää nähtäväksi, kykenevätkö 3G-verkot vastaamaan näihin haasteisiin. Työssä käsitellään 3G-verkon arkkitehtuuria, toimintaa ja puhelunohjausta MSC Server -konseptissa, sekä käydään läpi muutamia puheluesimerkkejä. 3G-verkon arkkitehtuuri, jossa puhelunohjaus on erotettu mediakerroksesta, esitetään ja uudet verkkoelementit ja niiden toiminta käsitellään. Esitelty teoria perustuu kirjallisuuteen sekä yleisesti hyväksyttyihin 3G- verkon standardeihin. Näitä standardeja julkaisevat muun muassa ITU-T ja 3GPP yhdessä yhteistyöyritystensä kanssa. Standardointityö on monin osin vielä kesken ja se on vaikeuttanut 3G-verkkojen suunnittelutyötä merkittävästi. Työn tarkoituksena on selvittää puhelunohjausta 3G-verkossa ja sen toteuttamista MSC Server –konseptilla. MSC Serverin toteutusvaihtoehtoja arvioidaan ja niistä valitaan yksi 3G-verkon puhelunohjauksen toteutusmalliksi. Työtä jatketaan tämän diplomityön jälkeen tarkemman toteutuksen suunnittelulla, päämääränä rakentaa 3G-verkko.

Informaation hallinta prosessiteollisuuden investointiprojektissa

Diplomityössä on tutkittu kohdeyrityksen, UPM-Kymmene Oyj Kymin tuotantoyksikön nykyisiä investointiprojektin tiedonhallinnan käytäntöjä. Nykytilan selvityksen ja haastatteluissa ilmenneiden tarpeiden perusteella on työssä esitelty uusi toimintamalli tulevia investointiprojekteja varten. Diplomityö perustuu aihepiirin kirjalliseen tarkasteluun ja yhteistyökumppaneiden haastatteluihin. Kirjallisuuden avulla on selvitetty dokumenttienhallinnan teoriaa ja tulevaisuuden näkymiä. Haastatteluilla on selvitetty Kymin tiedonhallinnan nykytilaa ja tulevia tarpeita. Haastatteluita on tehty Kymillä sisäisesti ja Kymin konsultti- ja laitetoimittajaosapuolten kanssa. Työssä käsitellään informaationhallintaa dokumenttienhallinnan ja erilaisten investointiprojektissa käsiteltävien dokumenttien pohjalta. Investointiprojektissa syntyvän talletettavan ja arkistoitavan dokumenttiaineiston lisäksi huomioidaan laitetietojen hallinta, mutta vain periaatteellisella tasolla. Investointiprojektin tiedonhallinnassa ehdotetaan siirryttävän perinteisestä eri projektiosapuolten keskinäisestä tiedonvaihdosta verkottuneeseen tiedonhallinnan malliin. Verkottuneessa tiedonhallinnassa toimitaan investointiprojektin osapuolten yhteisen tietovaraston avulla. Työn tuloksena syntynyt kohdeyrityksen toimintamalli koostuu useista eri osa-alueista, mikä mahdollistaa toimintamallin hyödyntämisen yksittäisiä osa-alueita kokonaisuudesta irrottamalla. Toimintamallia on mahdollista hyödyntää vastaavanlaisten tuotanto-laitosten investointiprojektien yhteydessä. Työssä toimintamallin käytännön sovellutus kohdeyrityksessä on esitetty käyttöönottoprojektina.

Object-Oriented Modelling of Multilayer Networks

Tämä diplomityökuuluu tietoliikenneverkkojen suunnittelun tutkimukseen ja pohjimmiltaan kohdistuu verkon mallintamiseen. Tietoliikenneverkkojen suunnittelu on monimutkainen ja vaativa ongelma, joka sisältää mutkikkaita ja aikaa vieviä tehtäviä. Tämä diplomityö esittelee ”monikerroksisen verkkomallin”, jonka tarkoitus on auttaa verkon suunnittelijoita selviytymään ongelmien monimutkaisuudesta ja vähentää verkkojen suunnitteluun kuluvaa aikaa. Monikerroksinen verkkomalli perustuu yleisille objekteille, jotka ovat yhteisiä kaikille tietoliikenneverkoille. Tämä tekee mallista soveltuvan mielivaltaisille verkoille, välittämättä verkkokohtaisista ominaisuuksista tai verkon toteutuksessa käytetyistä teknologioista. Malli määrittelee tarkan terminologian ja käyttää kolmea käsitettä: verkon jakaminen tasoihin (plane separation), kerrosten muodostaminen (layering) ja osittaminen (partitioning). Nämä käsitteet kuvataan yksityiskohtaisesti tässä työssä. Monikerroksisen verkkomallin sisäinen rakenne ja toiminnallisuus ovat määritelty käyttäen Unified Modelling Language (UML) -notaatiota. Tämä työ esittelee mallin use case- , paketti- ja luokkakaaviot. Diplomityö esittelee myös tulokset, jotka on saatu vertailemalla monikerroksista verkkomallia muihin verkkomalleihin. Tulokset osoittavat, että monikerroksisella verkkomallilla on etuja muihin malleihin verrattuna.