Pasi Luukka

Lappeenranta – Lahti University of Technology LUT · School of Business and Management

There is a lot of evidence of the manufacturing strategy shift from mass production to the individual and decentralized micro-production, which in essence means a shift from low-cost country production to production at the place of consumption. This paper presents a vision for a highly automated digital urban manufacturing network, based on a centr...

Additive manufacturing (AM) is a promising technology for designing complex metallic pieces for different sectors with resource and time effectiveness. Titanium (Ti) is an essential critical material for AM development. AM can produce intricate and cost-effective components with Ti alloys for the transportation sector which would not be possible wi...

In supervised machine learning applications, feature construction may be used to create additional, informative features with the aim to support the prediction of the target output. This study investigates the impact of feature construction, specifically the use of quadratic and interaction terms, on the predictive performance of a classifier. More...

Water-energy nexus studies aim to connect the process of power generation with the corresponding water demand. The lack of information on the currently installed cooling systems at individual power plants is a challenge for the assessment of the water use on the power plant-level, which complicates decision-making in water management, especially in...

In supervised machine learning applications, feature construction may be used to create additional, informative features with the aim to support the prediction of the target output. This study investigates the impact of feature construction, specifically the use of quadratic and interaction terms, on the predictive performance of a classifier. More...

The fuzzy k-nearest neighbor (FKNN) algorithm, one of the most well-known and effective supervised learning techniques, has often been used in data classification problems but rarely in regression settings. This paper introduces a new, more general fuzzy k-nearest neighbor regression model. Generalization is based on the usage of the Minkowski dist...

This paper proposes a novel framework based on a recently introduced classifier called multi-local power mean fuzzy k-nearest neighbor (MLPM-FKNN) and the Minkowski distance to classify biomass feedstocks into property-based classes. The proposed approach uses k nearest neighbors from each class to compute class-representative multi-local power mea...

This study investigates cause and effect relationships in cognitive maps and the coexistence of pairs of such relationships in cognitive maps of a chosen group of decision-makers. We call the existence of a pair of causal relationships shared by the group of decision-makers in their cognitive maps inter-causal relationship. We investigate the coexi...

Most of the studies investigating machine learning methods such as neural networks and their ability to forecast stock markets deploy a binary target (buy, sell). However, when trading strategies are implemented based on the prediction of a binary target, they can be vulnerable to misclassification and their overall return may also be more suscepti...

The lack of information on the current water demand of individual thermal power plants is a problem for the planning of future energy systems, especially in regions with high water scarcity and an elevated power demand. This lack is linked to the limited availability of data on the type of cooling technology for these power plants. In this study, w...

Traffic speed and traffic jam prediction are necessary for a successful regulation of traffic flow and also for the prevention of accidents. This chapter contributes to the body of knowledge on traffic characteristics prediction by focusing on the possibilities of traffic speed prediction in an urban area of a medium-sized European city—the Finnish...

We revisit the fuzzy similarity and entropy (FSAE) filter method for supervised feature selection and propose the C-FSAE filter method that only uses similarities of observations to their own class’s ideal vector (intra-class) and deploys a normalized scaling factor that accounts for the distance between ideal vectors normalized by the standard dev...

In this paper we propose three novel feature ranking methods for supervised feature selection in the context of classification which are based on possibility theory. All three methods – nonspecificity, strife and total uncertainty – are tested on eight artificial data sets and ten medical real-world data sets and benchmarked against ReliefF, the Fi...

In this paper we introduce a transformation of the center of gravity, variance and higher moments of fuzzy numbers into their possibilistic counterparts. We show that this transformation applied to the standard formulae for the computation of the center of gravity, variance, and higher moments of fuzzy numbers gives the same formulae for the comput...

This paper investigates relevant features for the prediction of intraday S&P 500 returns. In contrast to most previous research, the problem is approached as a four class classification problem to account for the magnitude of the returns and not only the direction of price movements. A novel framework for feature selection using a hybrid approach i...

In this literature review, we investigate machine learning techniques that are applied for stock market prediction. A focus area in this literature review is the stock markets investigated in the literature as well as the types of variables used as input in the machine learning techniques used for predicting these markets. We examined 138 journal a...

The transportation sector is responsible for the largest share (29% in 2019) of greenhouse gas emissions (GHG). One of the ways to reduce this share consists in introducing lightweight vehicles in order to diminish fuel consumption, and, in consequence, GHG emissions. Magnesium (Mg) carries considerable potential as a lightweight material to be use...

Extract summarization algorithms help identify significant information from the news by extracting meaningful sentences from the original text. The information background existing at the time of the news release often significantly affects its content. Such background can distort the text summarization algorithm working results. The study was condu...

We present a new generalized version of the fuzzy k-nearest neighbor (FKNN) classifier that uses local mean vectors and utilizes the Bonferroni mean. We call the proposed new method Bonferroni-mean based fuzzy k-nearest neighbor (BM-FKNN) classifier. The BM-FKNN classifier can be easily fitted for various contexts and applications, because the para...

This paper presents the first fully possibilistic method for real option valuation of investment projects, a new possibilistic variant of the fuzzy pay-off method for real option valuation. The new variant is derived by using the Luukka-Stoklasa-Collan transformation and is proven to be consistent with financial theory. The new variant is comparati...

Strategic management researchers have long been fascinated with company performance in terms of underlying managerial cognition and its interpretation. This paper presents a methodology to examine the linkage between the cognition of individuals and company performance. We link cognitive maps with fuzzy-set qualitative comparative analysis (fsQCA)...

Increasing pace of technological change in the energy sector towards more sustainable solutions has raised the importance of managers’ abilities to notice and interpret changes in their environments, and translate those perspectives into strategic choices. Consequently, this study aims to examine managerial interpretation on changing business envir...

In this paper we propose a novel feature selection method which is based on fuzzy measures. More specifically, we apply a similarity measure to form similarity matrices from the data and apply nonspecificity on similarity degrees in order to conduct feature selection. To measure how relevant a particular feature is, we apply an information transmis...

In this paper, we examine the concept of center of gravity and its relationship to the concept of possibilistic mean. We propose new transformations between the center of gravity and the possibilistic mean for triangular and trapezoidal fuzzy numbers.

This chapter discusses the multiple-criteria evaluation of innovations and new concepts by multiple experts under uncertainty that causes imprecision regarding the evaluations. The tools used are scorecards and fuzzy logic. The chapter presents for the first time how the lossless fuzzy weighted average (LFWA) can be used in the context of innovatio...

In many applications in machine learning, large quantities of features and information are available, but these can be of low quality. A novel filter method for feature selection for classification termed COLD is presented that uses class-wise clustering to reduce the dimensionality of the data. The idea behind this approach is that if a relevant f...

Stock markets can be interpreted to a certain extent as prediction markets, since they can incorporate and represent the different opinions of investors who disagree on the implications of the available information on past and expected events and trade on their beliefs in order to achieve profits. Many forecast models have been developed for predic...

This paper presents an extension of the fuzzy pay-off method for real option valuation using interval-valued fuzzy numbers. To account for a higher level of imprecision that can be present in many applications, we propose to use triangular upper and lower membership functions as the basis of real option analysis. In the paper, analytical formulas a...

This paper investigates the modified concepts of fuzzy consistency and fuzzy coverage recently proposed by Stoklasa et al. in the context of the fuzzified settheoretic approach for the purpose of linguistic/fuzzy rule validation in social sciences. The new fuzzified consistency and coverage measures (denoted by the F2 and F3 indices in the paper by...

A growing body of literature has examined cognitive maps using various methods for different purposes in different situations. This study aims to elicit and scrutinize cognitive maps which are based on interpretations of strategic issues, and evaluate the performances of the teams who contributed to produce cognitive maps. The research analyzes 431...

Likert scales have been in use since 1930s as tool for attitude expression in many fields of social science. Recently there have even been several attempts for the fuzzification of this instrument. In this chapter we explore the possibility of their use in multiple-criteria multi-expert evaluation. We focus on discrete fuzzy Likert scales, that are...

Banks are required by the Basel II Accord to report on their operational risks, including reporting an estimate for the size of possible one-off negative operational events. The typical way to produce these estimates is to use a quantitative value at risk methodology that is based on a limited amount of data, but also the use of qualitative, expert...

Large amounts of information and various features are in many machine learning applications available, or easily obtainable. However, their quality is potentially low and greater volumes of information are not always beneficial for machine learning, for instance, when not all available features in a data set are relevant for the classification task...

This chapter presents an analysis of how the new Russian support policy for renewable energy investments changes the expected profitability of renewable energy investments in Russia. A comparative analysis of investment profitability in the before and after support policy cases is presented for a wind farm investment to illustrate the effect of the...

This paper compares the efficacy of both traditional valuation ratios and an extensive set of related combination criteria in identifying the future best-performing stocks for a comprehensive U.S. sample over the period 1971–2013. Value portfolios formed on different criteria have remarkably different exposures to style factors. We find evidence of...

In the literature, researchers and practitioners can find a manifold of algorithms to perform a classification task. The similarity classifier is one of the more recently suggested classification algorithms. In this paper, we suggest a novel similarity classifier with multiple ideal vectors per class that are generated with k-means clustering in co...

Peer-assessment between students is a way to include evaluation as a part of the learning process and to simultaneously cut teacher load in grading of assignments. eLearning systems can be used to automate peer-assessment to a large extent. Peer-assessment benefits from multiple-peer-assessment as it is likely to even-out outliers. Linguistic score...

This paper proposes a new procedure for enriching investment and real option analysis performed with the fuzzy pay-off method by decomposing the pay-off distribution into multiple sub-distributions that correspond to different investment scenarios. This creates more information about the importance of the effect of selected factors to investment pr...

Design choices made early in the product development process have an important impact on the chances of product commercialization and on product success in general. These choices are typically multiple-criteria problems, where estimates about the goodness of each criterion often contain overlapping redundant information. Many multiple-criteria deci...

Giga-investments are large industrial investments that have long construction times, long economic lives, and that are to a large degree irreversible. These characteristics make ex-ante analysis of giga-investment difficult and require methods that can consider estimation of imprecision and the value of managerial flexibility. Fuzzy pay-off method...

This paper compares the efficacy of four multicriteria decision-making (MCDM) methods in identifying the future best-performing stocks in two comprehensive samples of U.S. stocks. This is the first time that median-scaling (MS), the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), the Analytic Hierarchy Process (AHP), and...

We introduce a new transformation of the variance function to possibilistic variance and vice versa. We show that the transformation of the center-of-gravity-based formulation of variance gives exactly the possibilistic variance introduced by Carlsson and Fullér and that the corresponding inverse transformation gives the original variance formula f...

This paper studies how the selection of the metal price process used and the choice of selected other modeling assumptions affect the value of a metal mining company’s mining asset portfolio. We compare results from when metal prices are assumed to be independent of each other, correlated with each other, and correlated with an external factor. The...

Realization of mine water management related risks can, e.g., cause temporary shutdowns of mining operations leading to decreased economic returns of metal mining operations. In this paper, a techno-economic system model for metal mines is applied to study this issue. The usability of the model is illustrated with a numerical simulation to analyze...

This paper studies the effects of financing conditions to managerial flexibility and project value and focuses on the point of view of the equity holder of a mining company. Simulation based analysis is performed with a dynamic system model of a metal mine investment. The leverage effect of the equity holder's discount rate change as a function of...

In this paper we present a new procedure for patent selection and ranking that uses a new dynamic consensus model and a new variant of the Matching Method real options framework. The procedure utilizes opinions from multiple experts in the creation of a stream of consensual yearly cash-flows for each patent. The cash-flow stream is used as an input...

The use of set-theoretic concepts of consistency and coverage and their fuzzified versions needs to be accompanied with an extension of the general (non-fuzzy) methodology. In the fuzzy context, the same piece of data can provide partial evidence in favour of the existence of a given relationship, and at the same time contribute to its disproof, wh...

Objective The objective of this study was to explore the potential of the Infant/Toddler Sensory Profile (ITSP) as a screening tool for autism spectrum disorders (ASD) in prematurely born children. Methods Parents of 157 children with birth weights <1,500 g (aged 2 years, corrected for prematurity; 88 boys, 69 girls) completed a screening battery...

Purpose The purpose of this paper is to demonstrate how managerial estimates of long-term market price trends can be included into investment analysis of metal mining. The inclusion of subjective market information with a new cycle reverting price process is proposed. Design/methodology/approach Subjective managerial estimates are included into st...

Histograms are an intuitively understandable tool for graphically presenting frequency data that is available for and useful in modern data-analysis, this also makes comparing histograms an interesting field of research. The concept of similarity and similarity measures have been gaining in importance, because similarity and similarity measures can...

This article introduces a new extension to fuzzy TOPSIS. In the extension we have used as a basis a fuzzy similarity based fuzzy TOPSIS that uses an additional component of multi-distance in forming a closeness coefficient. Ordered weighted averaging is also used in the aggregation process over fuzzy similarity values. For the ordered weighted aver...

This paper presents a new method to enhance simulation-based analysis of complex investments that contain multi-variable uncertainty. The method is called "simulation decomposition". Typically the result of simulation-based investment analysis is in the form of histogram distributions - here we propose a method for first classifying the possible ou...

Despite of increasing interest in social cognitive research in strategic management during recent years,few studies have examined the relationship between cognitive structures of top management and middlemanagement. This study represents the information processing approach in managerial cognition research assuming that top management communicate th...

This paper presents how a dynamic system model can be used together with the Datar–Mathews real option analysis method for investment analysis of metal mining projects. The focus of the paper is on analyzing a project from the point of view of the project owner. The paper extends the Datar–Mathews real option analysis method by combining it with a...

This article introduces a multi-criteria decision making (MCDM) method that takes into account interdependency of criteria. Recognizing information redundancy in related criteria the proposed approach offers their weight formation based on their interaction. Further, normalized estimated criteria and their weights are aggregated by means of Fuzzy H...

This extended abstract presents an extension of the fuzzy inference system framework for investment analysis with the fuzzy pay-off method. We build an add-on module that performs real option valuation. The new framework is able to reflect peculiarities of complex investment cases with complicated causal relationship of the influencing factors. Inc...

This workshop NSAIS´16 is the second one in the series of workshops organized by the North-European Society for Adaptive and Intelligent Systems (NSAIS). The first workshop took place more than ten years ago and this is the first international event organized by NSAIS ever since. The idea of this workshop is to be the beginning of a series of works...

We introduce a new n-ary λ similarity classifier that is based on a new n-ary λ-averaging operator in the aggregation of similarities. This work is a natural extension of earlier research on similarity based classification in which aggregation is commonly performed by using the OWA-operator. So far λ-averaging has been used only in binary aggregati...

This paper presents analysis of how the new Russian support policy for renewable energy investments pushes a real option to invest in generation of renewable energy within Russia into the money. A comparative analysis of before and after cases is presented based on a stylized system dynamic model of wind farm investment that is used as the basis fo...

This paper examines the profitability of index trading strategies that are based on dual moving average crossover (DMAC) rules in the Russian stock market over the 2003–2012 period. It contributes to the existing technical analysis (TA) literature by comparing for the first time in emerging markets the relative performance of individual stocks’ tra...

This paper presents a detailed system dynamic (SD) model of a metal mining investment that is usable in ex ante profitability and operations management analysis. We show how the SD model can be used to analyze the profitability effect of three operational real options: the option to temporarily close production, the option to abandon production, an...

Purpose The purpose of this paper is to examine the role of cognitive diversity on strategic issue interpretation among the boards of directors making sense of sustainability management. The study also investigated the centrality of the corporate sustainability issues to identify common interpretative patterns in the shared cognitive maps among the...

Strategic R&D projects require forward-looking analysis and face structural uncertainty, which means that most often precise and detailed information about them is unavailable. This means that any systems that are used in managing them must be robust enough to handle the available imprecise information, while at the same time being simple enough to...

In this paper, we introduce a new version of the well-known TOPSIS method: similarity-based TOPSIS. The new method uses a similarity measure to replace the commonly used distance measure. Similarity measure is formed under generalised £ukasiewicz structure that allows us to form the measure in a more general structure and this way enhances (patent)...

This paper introduces a new and innovative methodology for value portfolio selection by adjusting the conventional valuation ratios on the basis of firm size, financial leverage and industry classification and combining them as single selection criteria. The tercile portfolios are composed of a comprehensive sample of Finnish non-financial stocks b...

A similarity classifier based on Bonferroni mean based operators is introduced. The new Bonferroni mean based variant of the similarity classifier is also extended to cover a new Bonferroni-OWA variant. The new Bonferroni-OWA based similarity classifier raises the question of how to accomplish the weighting needed and for this reason we also examin...

This paper describes a new classification method that uses the differential evolution algorithm to find an optimal parameter selection for classification of objects. Parameters optimised include the distance measure used, distance parameters, class vectors for each class, and OWA-parameters. The distances yielded for each feature by the optimised d...

The paper compares numerically the results from two real option valuation methods, the Datar-Mathews method and the fuzzy pay-off method. Datar-Mathews method is based on using Monte Carlo simulation within a probabilistic valuation framework, while the fuzzy pay-off method relies on modeling the real option valuation by using fuzzy numbers in a po...

This paper presents a system dynamic techno-economic model of a metal mining investment. The model can be used for ex-ante and ex-post analysis of metal mining investment profitability management. The functionality of proposed model is numerically illustrated with a realistic ex-post analysis case, the given illustration shows how the level of work...

This article examines the profitability of dual moving average crossover (DMAC) trading strategies in the Russian stock market over the 2003–12 period. It contributes to the existing technical analysis (TA) literature by testing, for the first time, the applicability of ordered weighted moving averages (OWMA) as an alternative calculation basis for...

In this paper, we will present the firm’s knowledge base function and introduce an optimisation problem where the firm seeks to maximise its profits with scarce knowledge assets. In this, it has to share its knowledge assets between activities that help to increase the firm’s knowledge base and activities that are needed to protect and exploit the...

Renewable energy has become an actively developing sector in many emerging economies and there are various incentive mechanisms. Russia has implemented a unique incentive policy for renewable energy investments, based on two separate mechanisms that reduce the risks of investments into renewable energy generation. This study presents a short analys...