Rule groupings in expert systems using nearest neighbour decision rules, and convex hulls

Expert System shells are lacking in many areas of software engineering. Large rule based systems are not semantically comprehensible, difficult to debug, and impossible to modify or validate. Partitioning a set of rules found in CLIPS (C Language Integrated Production System) into groups of rules which reflect the underlying semantic subdomains of the problem, will address adequately the concerns stated above. Techniques are introduced to structure a CLIPS rule base into groups of rules that inherently have common semantic information. The concepts involved are imported from the field of A.I., Pattern Recognition, and Statistical Inference. Techniques focus on the areas of feature selection, classification, and a criteria of how 'good' the classification technique is, based on Bayesian Decision Theory. A variety of distance metrics are discussed for measuring the 'closeness' of CLIPS rules and various Nearest Neighbor classification algorithms are described based on the above metric

Evolving stochastic learning algorithm based on Tsallis entropic index

In this paper, inspired from our previous algorithm, which was based on the theory of Tsallis statistical mechanics, we develop a new evolving stochastic learning algorithm for neural networks. The new algorithm combines deterministic and stochastic search steps by employing a different adaptive stepsize for each network weight, and applies a form of noise that is characterized by the nonextensive entropic index q, regulated by a weight decay term. The behavior of the learning algorithm can be made more stochastic or deterministic depending on the trade off between the temperature T and the q values. This is achieved by introducing a formula that defines a time-dependent relationship between these two important learning parameters. Our experimental study verifies that there are indeed improvements in the convergence speed of this new evolving stochastic learning algorithm, which makes learning faster than using the original Hybrid Learning Scheme (HLS). In addition, experiments are conducted to explore the influence of the entropic index q and temperature T on the convergence speed and stability of the proposed method

Mixed Bag: Simulating Market-Based Instruments for Water Quality and Quantity in the Upper Waikato

We designed and implemented participatory computer simulations in three workshops in New Zealand's Upper Waikato catchment to learn how market-based instruments (MBIs) might improve freshwater outcomes when managing water and land resources within limits. An Excel-based platform was built to simulate, in stakeholder workshops, the use of transferable permits and user charges for both water quantity and water quality in the Upper Waikato catchment. Each participant managed a hypothetical property in a simplified catchment that included seven farms, a pulp mill, district council, and a hydro - electric company. Based on profit schedules and policy settings, participants made choices about production intensity, land use change and trading of water and/or nutrient allowances. The simulations highlighted the social and cultural context in which MBIs must operate, and how that context influences the outcomes that we can expect from MBIs. Participants found the simulations to be a valuable learning experience

Improved sign-based learning algorithm derived by the composite nonlinear Jacobi process

In this paper a globally convergent first-order training algorithm is proposed that uses sign-based information of the batch error measure in the framework of the nonlinear Jacobi process. This approach allows us to equip the recently proposed Jacobi–Rprop method with the global convergence property, i.e. convergence to a local minimizer from any initial starting point. We also propose a strategy that ensures the search direction of the globally convergent Jacobi–Rprop is a descent one. The behaviour of the algorithm is empirically investigated in eight benchmark problems. Simulation results verify that there are indeed improvements on the convergence success of the algorithm

Parliament/Funkadelic -yhtyeen bassonkäyttö : analogisyntetisaattori bassoinstrumenttina

Tutkielmani käsittelee yhdysvaltalaisen R&B -yhtye Parliament/Funkadelicin bassonkäyttöä. Tavoitteeni on selvittää, milloin, miten ja miksi yhtye siirtyi 1970-luvun puolivälissä analogisyntetisaattoreiden, erityisesti Minimoogin, käyttöön. Lisäksi pyrin selvittämään vaikuttiko Minimoog yhtyeen menestykseen ja sitä kautta tanssimusiikin kehitykseen. Samalla käyn tutkielmassani läpi funk- ja diskomusiikin historiaa. Selvitän myös lyhyesti analogisyntetisaattorin yleistymistä populaarimusiikissa 1960- ja 1970-luvun taitteessa. Tutkielmani lähteinä ja materiaalina käytän funk- ja diskomusiikin historiasta kertovaa kirjallisuutta. Lisäksi käytän lähteinä yhtä analogisynteesiin perustuvaa väitöskirjaa, verkkodokumentteja ja äänitteitä. Äänitteitä kuuntelemalla analysoin kappaleiden soitinvalintoja ja teen päätelmiä siitä, milloin yhtye on ottanut analogisyntetisaattorit osaksi sointiaan. Samalla pohdin mahdollisia syitä eri soitin- ja sointivalintoihin. Parliament/Funkadelic -yhtyeen äänitteet ovat suurin yksittäinen lähdemateriaali historiatutkielmassani. Tutkielmani peruskäsitteitä ovat Minimoog ja analogisyntetisaattorit, sähköbasso, bassolinjat ja sointivärit. Työni tuloksena huomasin, että yhtyeen soitinvalintaan vaikutti muusikoiden aikaisemmat sointimieltymykset ja efektikokeilut mutta myös syntetisaattoreiden uutuudenviehätys. Parliament/Funkadelic -yhtyeen jäsenet ja musiikintuottajat olivat uusien tuotantotapojen ja soittimien aikaisia omaksujia. Analogisyntetisaattorin sointiväri ja äänentuottotapa palveli paremmin sitä musiikkisuuntausta, mihin yhtye oli matkalla. Tutkielmaani voi soveltaa tiiviinä katsauksena ja tiedonlähteenä analogisyntetisaattorin yleistymisestä funk- ja tanssimusiikissa.The main topic of my research work is Parliament/Funkadelic’s use of bass. I aimed to figure out when, why and how the band began its shift towards using the analog synthesizer, especially the Minimoog, for producing bass lines. In addition I tried to find out if the Minimoog affected the band’s popularity and also if the band’s success had an impact on the course of dance music. I researched general history of dance and funk music. I also examined the analog synthesizer’s growth of popularity in the 1960s and 1970s. The key topics of my work are the Minimoog and analogue synthesizers, electric bass, bass lines and timbre. As my reference material I used literature based on the history of funk and dance music. My reference materials also included one dissertation on analog synthesis, internet documents and recordings. By listening to the recordings, I could hear what instruments the musicians had been using and also deduct when the band had started to use more and more synthesizers. By listening to the earlier recordings I tried to find reasons behind the choices in different instruments. The recordings were the biggest source of material in my history research work. As a result of my work I found that the band’s choices of instruments were affected by the musicians’ earlier preferences in sound and effect pedals. The new soundscape provided by the synthesizer certainly was a key factor. The members of Parliament/Funkadelic were early adopters of new musical instruments and ways to make music. The analogue synthesizer’s timbre and way to produce sound suited better the band’s new musical output. My research can be used as a brief and compact take on the growth of the analogue synthesizer in funk and dance music.CD -liite: Theseus.fi -julkaisussa ei ole mukana CD-liitettä