Genetic Algorithm Based Formula Generation for Curve Fitting in Time Series Forecasting Implemented as Mobile Distributed Computing

Ketipov, Rumen; Kostadinov, Georgi; Petrov, P.; Zankinski, Iliyan; Balabanov, Todor

doi:10.1007/978-3-030-55347-0_4

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…To be successful every company from the large organizations to family businesses needs well-planned information strategy [7]. Therefore, many different approaches are proposed to cope with different practical problems such as effective management in streetlight modernization [8], decision making in publishing sector [9] and selection of supplier under public procurement [10], for doing business [11] and business management [12], different real-life applications with time series forecasting [13], etc. The development of business information systems should be based on innovative models and computational intelligence methods.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Group Decision-Making Approach Considering Uncertainty Conditions

Borissova

Dimitrova

2021

Bus. Inf. Sys.

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The management of business information processes needs effective decision-making models. That means to involve different methods, techniques, and principles to improve competitiveness and to achieve the planned business results. In this context, the article deals with the problem of group decision-making under uncertain conditions. To cope with such problems some well-known optimization strategies of Wald, Laplace, Hurwitz, and Savage are modified to take into account the experts’ opinions with different importance when forming the final group decision. Numerical testing is based on a case study for CRM software selection. The results are discussed based on the proposed models under two different cases derived from the case study. The conducted numerical testing of the proposed models demonstrates their applicability to cope simultaneously with multiple experts’ evaluations and uncertainty conditions.

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Section: Introductionmentioning

confidence: 99%

An Integrated Group Decision-Making Approach Considering Uncertainty Conditions

Borissova

Dimitrova

2021

Bus. Inf. Sys.

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Cloud Data-Driven Intelligent Monitoring System for Interactive Smart Farming

Dineva

Atanasova

2022

Sensors

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Smart farms, as a part of high-tech agriculture, collect a huge amount of data from IoT devices about the conditions of animals, plants, and the environment. These data are most often stored locally and are not used in intelligent monitoring systems to provide opportunities for extracting meaningful knowledge for the farmers. This often leads to a sense of missed transparency, fairness, and accountability, and a lack of motivation for the majority of farmers to invest in sensor-based intelligent systems to support and improve the technological development of their farm and the decision-making process. In this paper, a data-driven intelligent monitoring system in a cloud environment is proposed. The designed architecture enables a comprehensive solution for interaction between data extraction from IoT devices, preprocessing, storage, feature engineering, modelling, and visualization. Streaming data from IoT devices to interactive live reports along with built machine learning (ML) models are included. As a result of the proposed intelligent monitoring system, the collected data and ML modelling outcomes are visualized using a powerful dynamic dashboard. The dashboard allows users to monitor various parameters across the farm and provides an accessible way to view trends, deviations, and patterns in the data. ML models are trained on the collected data and are updated periodically. The data-driven visualization enables farmers to examine, organize, and represent collected farm’s data with the goal of better serving their needs. Performance and durability tests of the system are provided. The proposed solution is a technological bridge with which farmers can easily, affordably, and understandably monitor and track the progress of their farms with easy integration into an existing IoT system.

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Genetic Algorithm Based Formula Generation for Curve Fitting in Time Series Forecasting Implemented as Mobile Distributed Computing

Cited by 2 publications

References 11 publications

An Integrated Group Decision-Making Approach Considering Uncertainty Conditions

An Integrated Group Decision-Making Approach Considering Uncertainty Conditions

Cloud Data-Driven Intelligent Monitoring System for Interactive Smart Farming

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