Fuzzy cognitive networks with functional weights for time series and pattern recognition applications

Karatzinis, Georgios; Boutalis, Yiannis S.

doi:10.1016/j.asoc.2021.107415

Cited by 15 publications

(5 citation statements)

References 55 publications

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“…The new scheme retains the good convergence characteristics of FCM but reduces the memory and computing requirements of using large fuzzy rule databases and unavoidable human intervention. Its performance is better than other well-known machine learning models (Karatzinis & Boutalis, 2021). Hedayat et al aim to apply fuzzy neural network (FNN) and Topsis integration method to explore zinc and lead resources and use FNN for geological, telemetry, geophysical, and geochemical data.…”

Section: Discussionmentioning

confidence: 99%

The design of intelligent fuzzy cognitive system of music emotion by product supply chain management

Jiang

2023

Expert Systems

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The classification of musical emotion is a challenging problem due to the subjectivity of human perception. In order to analyse the emotion contained in music from the perspective of product supply chain management, the psychological model and characteristics of music emotion are introduced. Additionally, the current product supply chain and the composition of the two contracts are analysed based on the characteristics of online music products. Finally, a speech emotion recognition model based on a Fuzzy Cognitive Map (FCM) is proposed. Two corpora containing five emotions (sadness, anger, happiness, surprise, and boredom) are selected to test the performance and characteristics of the network. In order to evaluate the system performance, different acoustic features are extracted, including prosodic features, formant features, marginal spectral features, and Mel‐Frequency Cepstral Coefficients (MFCC). The results show that the average recognition rate of MFCC features on the Berlin emotional speech database is 70.36%, which is 0.75% higher than the second‐highest edge spectrum features and achieves better results. Meanwhile, on this database, the Musical Emotion Recognition System based on FCM (MERS‐FCM) is improved by 20.36%, 7.34%, and 4.12% compared with Back Propagation, K‐nearest neighbour, and support vector machine, respectively, which shows that MERS‐FCM has better performance. The research of the music emotion recognition system based on FCM can provide more reference paths for the use and development of music emotion information.

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Section: Discussionmentioning

confidence: 99%

The design of intelligent fuzzy cognitive system of music emotion by product supply chain management

Jiang

2023

Expert Systems

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“…The concepts and weight values can be of a positive or negative form as the problem domain or experts may detect [8], [10]. The inference procedure takes the form of Equation (1.1) or (1.2) [24], [25]. The equation in 1.1 is a model of self-looping or a system with memory which is common in most FCM models.…”

Section: Fcm Formulationmentioning

confidence: 99%

“…Application Area Source Engineering and industrial process control [21], [16], [52], [53], [54] Pattern Recognitions [55], [24], Robotic Artificial Emotion [56]…”

Section: Table 2 Application Areas Of Fcmmentioning

confidence: 99%

A Review of Fuzzy Cognitive Maps Extensions and Learning

Jiya¹,

Georgina

2023

Journal-ISI

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Fuzzy Cognitive Maps (FCM) is a soft computing technique whose vertices and edges are fuzzy values with an inference mechanism for solving modelling problems; it has been used in modelling complex systems like industrial and process control. The concept was first introduced in 1986, with an initial learning algorithm in 1996; several works have been published on FCM methodology, learnings and applications. Fuzzy cognitive maps continue to evolve both in theory, learning algorithms and application. Many theories like intuitionistic theory, hesitancy theory, grey system theory, wavelet theory, etc., are integrated with the conventional FCM. These extensions have improved Fuzzy cognitive Maps to handle problems of uncertainty, incomplete information, hesitancy, dynamic systems and probabilistic fuzzy events. They also strengthen fuzzy cognitive Maps’ modelling power for application in almost any domain. However, the compilation of the development in methodology and adaptation of FCM are either old or omitted some of the recent advances or focused on specific applications of FCM in some areas. This paper reports extension, learning and applications of FCM from the initial conventional FCM to recent extensions and some of the important features of those extensions and learning.

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“…Pattern recognition is one powerful area that AI has thrived. Machine learning algorithms are employed to recognize patterns in a large volume of data (Karatzinis & Boutalis, 2021). Sorting several cases into categories or finding pattern in a case with large volume of information could be a daunting task; however, AI application like 'eDiscovery' being used in American courts performs intelligent analysis of case files before the start of a court procedure (Reiling, 2020).…”

Section: Extracting Patterns In Case Filesmentioning

confidence: 99%

Artificial Intelligence and Technology for Improving the Efficiency of The Judiciary in Nigeria

Jiya,

Samaila,

Surajo

2023

IJRIAS

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Technology is an essential component of the civilization of twenty-first-century society and one of the key forces influencing public sector organizations. Public infrastructures like transportation systems and important service delivery are managed using technology and powerful computing software. Artificial intelligence (AI) on the other hand helps to add intelligence to computing devices and applications through learning, reasoning, and perceiving things from data. However, the level of adoption or application of these technologies in the Nigerian judiciary seems to be low as seen during the covid-19 outbreak. The closed down of courts led to an increase in the backlog of cases due to the suspension of court proceedings. Even the option of filling cases using technology like WhatsApp could not function effectively. AI can This paper identifies some areas technology and AI can improve the performance of Nigeria’s judiciary and increase the speed of justice dispensation.

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Fuzzy cognitive networks with functional weights for time series and pattern recognition applications

Cited by 15 publications

References 55 publications

The design of intelligent fuzzy cognitive system of music emotion by product supply chain management

The design of intelligent fuzzy cognitive system of music emotion by product supply chain management

A Review of Fuzzy Cognitive Maps Extensions and Learning

Artificial Intelligence and Technology for Improving the Efficiency of The Judiciary in Nigeria

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