Improving Production in Small and Medium Enterprises

Knowledge management has gained relevance during the last years to improve business functioning. However, there is still a growing need of developing innovative tools that can help small to medium sized enterprises to detect and predict undesired situations. This article present a multi-agent system aimed at detecting risky situations. The multi-agent system incorporates models for reasoning and makes predictions using case-based reasoning. The models are used to detect risky situations and an providing decision support facilities. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented

Improving Gene Selection in Microarray Data Analysis Using Fuzzy Patterns Inside a CBR System

In recent years, machine learning and data mining fields have found a successful application area in the field of DNA microarray technology. Gene expression profiles are composed of thousands of genes at the same time, representing complex relationships between them. One of the well-known constraints specifically related to microarray data is the large number of genes in comparison with the small number of available experiments or cases. In this context, the ability to identify an accurate gene selection strategy is crucial to reduce the generalization error (false positives) of state-of-the-art classification algorithms. This paper presents a reduction algorithm based on the notion of fuzzy gene expression, where similar (co-expressed) genes belonging to different patients are selected in order to construct a supervised prototype-based retrieval model. This technique is employed to implement the retrieval step in our new gene-CBR system. The proposed method is illustrated with the analysis of microarray data belonging to bone marrow cases from 43 adult patients with cancer plus a group of three cases corresponding to healthy persons

A Multiagent System For Web-Based Risk Management in Small and Medium Business

Business Intelligence has gained relevance during the last years to improve business decision making. However, there is still a growing need of developing innovative tools that can help small to medium sized enterprises to predict risky situations and manage inefficient activities. This article present a multiagent system especially conceived to detect risky situations and provide recommendations to the internal auditors of SMEs. The core of the multiagent system is a type of agent with advanced capacities for reasoning to make predictions based on previous experiences. This agent type is used to implement an evaluator agent specialized in detect risky situations and an advisor agent aimed at providing decision support facilities. Both agents incorporate innovative techniques in the stages of the CBR system. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented

Multi-agent neural business control system

Small to medium sized companies require a business control mechanism in order to monitor their modus operandi and analyse whether they are achieving their goals. A tool for the decision support process was developed based on a multi-agent system that incorporates a case-based reasoning system and automates the business control process. The case-based reasoning system automates the organization of cases and the retrieval stage by means of a Maximum Likelihood Hebbian Learning-based method, an extension of the Principal Component Analysis which groups similar cases by automatically identifying clusters in a data set in an unsupervised mode. The multi-agent system was tested with 22 small and medium sized companies in the textile sector located in the northwest of Spain during 29 months, and the results obtained have been very satisfactory

A multi-agent system for web-based risk management in small and medium business

Business Intelligence has gained relevance during the last years to improve business decision making. However, there is still a growing need of developing innovative tools that can help small to medium sized enterprises to predict risky situations and manage inefficient activities. This article present a multi-agent system especially created to detect risky situations and provide recommendations to the internal auditors of SMEs. The core of the multi-agent system is a type of agent with advanced capacities for reasoning to make predictions based on previous experiences. This agent type is used to implement a evaluator agent specialized in detect risky situations and an advisor agent aimed at providing decision support facilities. Both agents incorporate innovative techniques in the stages of the CBR system. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented

Detección automática de momentos de risco alérxico da poboación ourensá

Na actualidade, o número de persoas que presentan reaccións alérxicas ao pole aumentou considerablemente, polo que é interesante contar con mecanismos que permitan determinar, coa maior precisión posible, a cantidade de pole que estará presente na atmosfera e reducir, deste xeito, o seu impacto na poboación. Para predicir a concentración de pole realizáronse estudos que utilizan modelos de regresión lineal e que, posteriormente, evolucionaron cara a modelos automáticos ou de aprendizaxe profunda. A pesar da aplicación idónea destes modelos para predicir a concentración de pole, os resultados obtidos dependen en gran medida da existencia de medicións previas de concentración e están influenciados pola calidade dos datos dispoñibles. A investigación conxunta das disciplinas de botánica e de informática trata de realizar unha estimación do risco de alerxias polo pole, de forma que permita a administración de antihistamínicos con anterioridade á súa exposición, posto que está demostrado que é moito máis efectiva ca unha vez aparecidos os primeiros síntomas. En concreto, esta estimación fíxose sobre Alnus, Betula, Platanus, Poaceae e Urticaceae, os cinco tipos de pole considerados máis agresivos na provincia de Ourense. O grupo de investigación da disciplina de botánica encargouse da captación de datos de concentración de pole, normalización e representación dos valores de recollida, calculou a estación polínica principal para cada tipo de pole e propuxo un calendario polínico para a cidade de Ourense. E o grupo de investigación de Informática centrouse na análise dos datos proporcionados e na comparación de diferentes técnicas de aprendizaxe automática para clasificar as concentracións de pole na atmosfera da provincia de Ourense e para facilitar a toma de decisións. Neste traballo móstrase a experimentación unicamente co tipo de pole Alnus; é de esperar que tamén será adecuada para cada un dos outros tipos de pole, adaptando en cada caso o modelo máis axeitado

Autonomous Internal Control System for Small to Medium Firms

Small to medium enterprises require an internal control mechanism in order to monitor their modus operandi and to analyse whether they are achieving their goals. A tool for the decision support process has been developed based on a case-based reasoning system that automates the internal control process. The objective of the system is to facilitate the process of internal auditing. The system analyses the data that characterises each one of the activities carried out by the firm, then determines the state of each activity, calculates the associated risk, detects the erroneous processes, and generates recommendations to improve these processes. The developed model is composed of two case-based reasoning systems. One is used to identify the activities that may be improved and the other to determine how the activities could be improved. Each of the two subsystems uses a different problem solving method in each of the steps of the reasoning cycle. The system has been tested in 22 small and medium companies in the textile sector, located in the northwest of Spain during the last 29 months and the results obtained have been very encouragin