Integrating Transfer Learning with Neutrosophic Weighted Extreme Learning Machine for Violence Detection in Smart Cities

Nigora Khaytboeva; Sergey Bakhvalov; Veronika Denisovich; Rafina Zakieva

doi:https://doi.org/10.54216/IJNS.250136

International Journal of Advances in Applied Computational Intelligence | 2024

Whale Optimization Algorithm with Deep Learning based Indoor Monitoring of Elderly and Disabled People

Social isolation and loneliness are subjective measures related to the feeling of distress and discomfort for disabled and elderly people. Currently, computing platform offers a smart healthcare observing technique for earlier fall detection. Internet of Things (IoT) based health system had a crucial role in the healthcare service and assists in improving data processing and its prediction. Transmitting data or reports takes more energy and time, as well as causes energy issues and higher latency. These study concentrations on the development of Whale Optimization Algorithm with Deep Learning based Indoor Monitoring System (WOADL-IMS) for Elderly and Disabled People. The presented WOADL-IMS system purposes to identify the presence of indoor activity by elderly people. In the presented WOADL-IMS technique, NASNetMobile model is applied to produce feature vectors. In addition, the WOADL-IMS technique uses WOA based hyperparameter selection approach. Finally, triplet neural network (TNN) model can be employed for automated classification and recognition of indoor activity. The simulation result of the WOADL-IMS approach can be examined on indoor activity dataset. The outcomes of the experimentation highlighted that the WOADL-IMS technique reaches better results than other recent approaches  

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Taher Ahmed Jubbori mail -

Ahmad Khaldi mail -

Karla Zayood mail

link https://doi.org/10.54216/IJAACI.050202

Volume & Issue

Vol. Volume 5 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2025

A New Deneutrosophication Method Proposal for Use in Delphi Methods: Application in Ancestral Knowledge Analysis

This study explores the rich cultural heritage of indigenous peoples and communities, whose traditions and adaptability have intrigued scholars interested in understanding their relevance in modern times. The Neutrosophic Delphi Method emerges as a vital tool in this research, offering a dynamic and versatile approach to address the inherent complexity of indigenous activities. By investigating the uncertainty and ambiguity in decision-making, this method enables a thorough examination of cultural practices. The interdisciplinary methodology employed focuses on the interaction between traditional and modern aspects, examining the main activities that define the daily lives of indigenous communities. The use of the Neutrosophic Delphi Method is highlighted for its ability to handle diverse perspectives and complex data, and the deneutrosophication process to improve precision and clarity in the findings. This technique ensures an accurate and harmonized representation of indigenous knowledge with modern scientific research. This effort seeks not only to enhance the academic legacy but also to foster international dialogue, promoting the recognition and appreciation of cultural diversity. By empowering indigenous populations to contribute to the generation of knowledge about their experiences, the study advocates for a more inclusive and equitable approach in scientific inquiry, acknowledging the invaluable contributions of indigenous communities to the cultural richness of our world.

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Edwin Fabián Cerda Andino mail -

Gabriela Beatriz Arias Palma mail -

Sanjar Mirzaliev mail

link https://doi.org/10.54216/IJNS.250129

Volume & Issue

Vol. Volume 25 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

Neutrosophic Approach to Increasing Production in Small Guinea Pig Breeding Systems: Exploring Tree Soft Set

The article examines the neutrosophic approach as an innovative tool to optimize production in small guinea pig farming systems. Through the exploration of bipolar sets and interval values, the application of this methodology in improving breeding processes is investigated, thus identifying areas of improvement and opportunities for economic and sustainable growth in the sector. The research highlights the importance of considering the uncertainty and imprecision inherent in these systems, proposing a flexible and adaptive framework that allows informed and strategic decision making to increase productivity and profitability. Likewise, the study highlights the need for a holistic and multidisciplinary understanding of the challenges and opportunities in guinea pig farming, recognizing the complexity of the social, economic, and environmental factors involved. Through an interdisciplinary approach, we seek to integrate traditional knowledge and practices with innovative approaches, thus promoting sustainability and the well-being of both producers and animals. Ultimately, this article offers a comprehensive and dynamic perspective on how the neutrosophic approach can significantly contribute to the development and optimization of guinea pig farming systems, thereby driving progress and prosperity in the agricultural sector.

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Luis A. Chicaiza Sánchez mail -

Patricia M. Andrade Aulestia mail -

César R. Delgado Acurio mail -

Rafael A. Garzón Jarrín mail -

Xavier C. Quishpe Mendoza mail

link https://doi.org/10.54216/IJNS.250132

Volume & Issue

Vol. Volume 25 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

An Innovative Approach to Financial Distress Prediction Using Relative Weighted Neutrosophic Valued Distances

The financial constraints of companies listed jeopardize the interests of employees and internal managers but also carries significant threats to outer investor and other stakeholders. Thus, there is need to create an effective financial distress predictive system.  The two most pressing issues in finance are assessing credit risk and predicting bankruptcies. Thus, credit scoring and financial distress prediction remain crucial areas of research in the financial industry. Previous research has aimed at the design of ML and statistical approaches to predict the financial distress of the company. Neutrosophic set may be utilized, which is a generality of classical, fuzzy, and intuitionistic fuzzy sets (IFS). They establish a foundation for addressing inconsistency, indeterminacy, and uncertainty associated with real-world challenges. This study presents an Innovative Approach to Financial Distress Prediction using Relative Weighted Neutrosophic Valued Distances (IAFDP-RWNVD) technique. The IAFDP-RWNVD technique intends to estimate the occurrence of financial distress in any firm or organization. In the IAFDP-RWNVD technique, two major processes are comprised. At the primary stage, the IAFDP-RWNVD technique applies RWNVD technique for the identification of financial distress. In the second stage, the IAFDP-RWNVD technique designs fish swarm algorithm (FSA) for finetuning the RWNVD model. The experimental outcomes of the IAFDP-RWNVD method is investigated using distinct aspects. The experimentation outcome shows the improvements of the IAFDP-RWNVD technique.

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Ilyоs Abdullayev mail -

Eduard Osadchy mail -

Natalya Shcherbakova mail -

Irina Kosorukova mail

link https://doi.org/10.54216/IJNS.250133

Volume & Issue

Vol. Volume 25 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2025

Soil Organic Transformations in Urban Agricultural Systems: Application of a Neutrosophic Multicriteria Approach for Comprehensive Evaluation

This study highlights the importance of urban agriculture in ensuring food security and promoting sustainability in urban areas, using a neutrosophic multi-criteria approach to evaluate the impact of biostimulants and organic additives on soil quality, plant growth, and crop yields. The research demonstrates that biofertilizers such as Chromococcus and Azotobacter significantly improve nutrient availability and plant health, resulting in robust and high-quality harvests, while mineral additives like zeolites enhance soil fertility and moisture retention. Three scenarios were analyzed using neutrosophic logic to handle the inherent uncertainty in urban agricultural systems: the first scenario shows exceptional plant growth and yield with high sustainability (valued as "Very Very High" according to neutrosophic logic), the second scenario highlights challenges in vegetative growth and sustainability (valued as "Low"), and the third scenario combines good plant growth with high sustainability and significant contributions to climate change mitigation (valued as "Medium High"). In summary, integrating organic amendments and biofertilizers in urban agriculture, evaluated through neutrosophic methods, is essential for creating resilient and productive agricultural systems, benefiting soil health, biodiversity, resource conservation, and local economies.

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Paolo Chasi Vizuete mail

link https://doi.org/10.54216/IJNS.250130

Volume & Issue

Vol. Volume 25 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

Evaluation of the Use of Whey in the Production of Aromatized Beverages by Neutrosophic Multicriteria Analysis

In this study, a thorough evaluation of the impact of whey use in the production of flavored beverages was carried out, using the neutrosophic analysis of variance method as the central research tool· The research focused on analyzing how whey, a byproduct of cheese production, could be used effectively in the production of flavored beverages, exploring its possible benefits and challenges from a comprehensive and multidisciplinary perspective· Through a series of experiments and exhaustive analyses, different variants of flavored beverages were examined, evaluating both their sensory quality and physical-chemical stability, and compared with beverages made without whey, revealing valuable insights about their viability and potential in the beverage industry· food and drinks· The findings of this study not only offer a deeper understanding of the role of whey in the production of flavored beverages, but also highlight the importance of the variance neutrosophic approach in evaluating this complex relationship· By integrating sensory analyzes with physicochemical measurements and stability considerations, a holistic and accurate picture of the effects of whey on the quality and characteristics of beverages could be obtained· These results not only have practical implications for the food industry, but also contribute to the advancement of research in multidimensional analysis methods and their application in the evaluation of innovative and sustainable food products.

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Zoila Eliana Zambrano Ochoa mail -

Gabriela Beatriz Arias Palma mail -

Carmen Amelia Cando Condorcana mail -

Jhony Daniel Lema Ramos mail

link https://doi.org/10.54216/IJNS.250131

Volume & Issue

Vol. Volume 25 / Iss. Issue 1

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Journal of International Economics Research | 2026

Evaluating the Effectiveness of the Paris Agreement and Challenges to International Climate Cooperation: A Political, Economic, and Justice-Based Analysis

The Paris Agreement (2015) marked a significant change in international climate regulation, as it does not have binding targets and instead contains a flexible, bottom-up system of nationally determined contributions (NDCs). Although this construction ensured almost universal participation, its use of voluntary commitments and lax implementation schemes has constrained its capacity to achieve the profound, fair cuts in emissions to curb warming to 1.5C. This study critically analyzes the effectiveness of the Agreement, its institutional structure, the dynamics of ambition, transparency framework, Article 6 market mechanism and finance. Basing his analysis on the prominent scholarly works, global climatic evaluation, and documentation undertaken by the UN, the analysis recognizes political self-interest, economic inequalities, unresolved differentiation, and finance gaps as key obstacles to real international collaboration. These structural vices are more impactful in developing countries. By examining Uzbekistan, a climate-vulnerable, and lower-middle-income Central Asian nation engaged in Article 6, this paper shows how the global challenges are being reflected at national levels, such as conditional NDCs, MRV capacity limitations, and reliance on outside assistance. The results highlight that in the absence of enhanced accountability, scaled and predictable climate finance, operationalized equity under CBDRRC, and hybrid governance, the Paris framework may stay aspirational, as opposed to transformative. The policy recommendations aim to achieve convergence in Article 6, improve domestic surveillance, and apply the principles of just transition to bridge the ambition and equity gap.

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Freshta Qauomy mail -

Salimova Sevara mail

link https://doi.org/10.54216/JIER.040203

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2025

Exploring Intuitionistic Fuzzy-Valued Neutrosophic Multiset Technique for High-Dimensional Financial Data Classification in Complex Systems

In decision-making, neutrosophic set allows for the information representation with three membership functions: truth (T), indeterminacy (I), and false (F). Each component in a neutrosophic set has membership, non-membership, and indeterminacy degrees that are independent and range from 0 to 1. This makes neutrosophic set especially suitable in complex decision-making scenarios where information is contradictory, incomplete, or ambiguous, which enables robust and more nuanced analysis and solutions. A large portion of finance companies experience problems handling vast amounts of data. These data are often left unstructured and unorganized. Therefore, it is necessary to classify them to exploit it. Data classification also simplifies to use, locating, and retrieval of information. It becomes vital while handling risk management, legal discovery, data security, and compliance. Therefore, this manuscript presents an Intuitionistic Fuzzy-Valued Neutrosophic Multiset based Financial Data Classification (IFVNMS-FDC) technique in Complex Systems. The main aim of the IFVNMS-FDC technique is to recognize and categorize the financial data into respective classes. To do so, the IFVNMS-FDC technique initially uses min-max scalar as a pre-processing step. Besides, the high-dimensional financial data can be handled by the design of whale optimization algorithm (WOA) based feature selection. Finally, the IFVNMS-FDC technique derives IFVNMS technique for the identification of various classes related to the financial data. A wide-ranging experiments were involved in exhibiting the performance of the IFVNMS-FDC technique. The experimental values depicted that the IFVNMS-FDC method obtains reasonable performance on financial data recognition.

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Hafis Hajiyev mail -

Emil Hajiyev mail -

Zarnigor Ilkhamova mail -

Elena Klochko mail -

E. Laxmi Lydia mail

link https://doi.org/10.54216/IJNS.250134

Volume & Issue

Vol. Volume 25 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

Harnessing Single-Valued Linguistic Complex Neutrosophic Set based Arabic Sentiment Classification on Natural Language Processing

Neutrosophic logic (NL) goes further by introducing a third component: indeterminacy. Each logical proposition in NL belongs to three degrees: truth (T), indeterminacy (I), and false (F), each taking value within the range of zero and one. This allows the processing and representation of uncertain, incomplete, and inconsistent data in a superior way. NL finds it beneficial in partially contradictory, partially known, and partially unknown scenarios, it becomes an effective instrument for applications in fields such as information fusion, artificial intelligence, and data analysis, where logical framework might be unsuccessful in handling the nuances and complexities of real-time data. Recently, Arabic sentiment analysis has become a hot research topic, which mainly intends to recognize sentiments that exist in Arabic social media. Therefore, this study introduces a Single-Valued Linguistic Complex Neutrosophic Set based Arabic Sentiment Classification (SVLCNS-ASC) technique on NLP applications. The presented SVLCNS-ASC technique undergoes Arabic data pre-processing and Glove word embedding process. For sentiment recognition, the SVLCNS-ASC technique applies the SVLCNS model, which enables to identification of various kinds of sentiments. At last, the performance of the SVLCNS model can be boosted by the use of artificial bee colony (ABC) based parameter-tuning approach. The results of the SVLCNS-ASC system has been studied on Arabic database. The experimental values indicate the supremacy of the SVLCNS-ASC approach compared to recent models.

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Aigul Sushkova mail -

Alfiya Yarullina mail -

Leysan Akhmetova mail -

Barno Shamuratova mail -

E. Laxmi Lydia mail

link https://doi.org/10.54216/IJNS.250135

Volume & Issue

Vol. Volume 25 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2025

Integrating Transfer Learning with Neutrosophic Weighted Extreme Learning Machine for Violence Detection in Smart Cities

Neutrosophic logic extends conventional and fuzzy logic (FL) by integrating the concepts of indeterminacy, truth, and falsity, enabling for a further extensive management of uncertainty. In classical binary logic, a statement can be either true or false. FL extends this by adding degree of truth, where a statement is partially true or false. The smart city technology shown to be an effective solution to the problems regarding improved urbanization. The practical applications of a smart city technology to video surveillance relies on the ability of processing and gathering large quantities of live urban data. Violence detection is considered as a major challenge in smart city monitoring.  The required computational power is substantial due to the large volume of video data gathered from the extensive camera network. As a result, the algorithm based on handcrafted features utilizing video and image processing fails to provide a promising solution. Deep Learning (DL) and Deep Neural Networks (DNNs) models are more reliable to handle these data. In this study, we introduce a Transfer Learning with Neutrosophic Weighted Extreme Learning Machine for Violence Detection (TL-NWELMVD) technique in smart cities. The TL-NWELMVD technique aims to recognize the presence of the violence in the smart city environment. In the TL-NWELMVD technique, the features can be extracted using SE-RegNet model. To enhance the performance of the TL-NWELMVD technique, a hyperparameter optimizer using monarch butterfly optimization (MBO) is involved. Finally, the NWELM classifier is applied for the identification of violence in the smart city environment. To investigate the accomplishment of the TL-NWELMVD technique, a widespread investigational outcome is involved. The simulation results portrayed that the TL-NWELMVD technique gains better performance compared to other models.

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Nigora Khaytboeva mail -

Sergey Bakhvalov mail -

Veronika Denisovich mail -

Rafina Zakieva mail

link https://doi.org/10.54216/IJNS.250136

Volume & Issue

Vol. Volume 25 / Iss. Issue 1

Details open_in_new