International Journal of Knowledge-Based and Intelligent Engineering Systems最新文献_第6页

Assessment of open-pit captive limestone mining areas using sentinel-2 imagery with spectral indices and machine learning algorithms 利用带有光谱指数和机器学习算法的sentinel-2图像评估露天圈养石灰石矿区

IF 0.7

International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2023-08-14 DOI: 10.3233/kes-230065

V. C., U. G

{"title":"Assessment of open-pit captive limestone mining areas using sentinel-2 imagery with spectral indices and machine learning algorithms","authors":"V. C., U. G","doi":"10.3233/kes-230065","DOIUrl":"https://doi.org/10.3233/kes-230065","url":null,"abstract":"Limestone mining is a significant economic activity in India, accounting for around 10% of the GDP however, it has certain negative environmental consequences. The objective of this study is to determine the spatial distribution area of captive limestone mines using remote sensing datasets, spectral index, and machine learning algorithms and compare their area estimation with industrial field survey reports for the financial year 2019. The study area includes a limestone resource area of 2226.16 ha with an excavation area of 487.10 ha in 2019. In the present research, we used a high-resolution Sentinel-2A satellite dataset to map and compute the active mining area by implementing the Normalised Vegetation Index (NDVI), Iterative Self-Organizing Data Analysis Technique (ISODATA), K-Nearest Neighbours (KNN), and Random Forest (RF) algorithms in the QGIS 3.18 software tool. The RF classifier estimated a limestone mine area of 379.57 ha with user accuracy (UA) of 97.25% and producer accuracy (PA) of 99.18% with a kappa coefficient value of 0.957. The mine area was estimated at 417.47 ha with a UA of 98.99% and PA of 99.10% and kappa value of 0.947 of the KNN method, The NDVI method estimated 469.92 ha with a UA of 93.63% and PA of 92.04% and kappa value 0.685. This research confirmed that the RF classifier well performed in classification with overall accuracy (OA) of 95.79% to KNN (OA of 94.78%), NDVI (OA of 79.84%) classifiers, and ISODATA poor in classification with OA of 64.16%. This research assists limestone mine owners and environmental engineers in making environmentally sustainable decisions, eco-friendly mine design, and monitoring.","PeriodicalId":44076,"journal":{"name":"International Journal of Knowledge-Based and Intelligent Engineering Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77799449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detection and elimination of multicollinearity in regression analysis 回归分析中多重共线性的检测与消除

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International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2023-07-13 DOI: 10.3233/kes-221622

Preeti Singh, Sarvpal H. Singh, M. Paprzycki

引用次数: 1

Selection of peanut butter machine by the integrated PSI-SV-MARCOS method 采用集成PSI-SV-MARCOS方法选择花生酱机

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International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2023-07-13 DOI: 10.3233/kes-230044

Melike Toslak, A. Ulutaş, Salim Ürea, Željko Stević

{"title":"Selection of peanut butter machine by the integrated PSI-SV-MARCOS method","authors":"Melike Toslak, A. Ulutaş, Salim Ürea, Željko Stević","doi":"10.3233/kes-230044","DOIUrl":"https://doi.org/10.3233/kes-230044","url":null,"abstract":"Production enterprises are enterprises that produce goods or services that aim to meet human needs such as machinery-equipment materials and labour. In order for a manufacturing enterprise to carry out its activities successfully, it must make the right choice when choosing its inputs. The correct execution of production activities and the selection of machinery, which requires high capital investments, also affect the efficiency of the enterprises, the correct use of materials and their costs. Therefore, it is an important decision for business managers to choose the right machine. At this stage, multi-criteria decision making (MCDM) methods are used for choosing the right machine. MCDM methods are methods used in the evaluation of alternatives using more than one criterion. In addition, the MCDM method is used in machine selection as well as in many areas. In this study, PSI, SV and MARCOS methods, which are among the MCDM methods, were used for peanut butter machine selection. First, the criteria and alternatives to be used for the peanut butter machine selection were determined by interviewing a peanut butter factory manager. In the study, while the criteria weights were determined, PSI and SV methods were used, while the machines were ranked with the MARCOS method. In addition, the MARCOS method was compared with other MCDM methods such as PIV, CODAS and WEDBA methods. After the rankings were found according to the methods, the relations between the rankings were examined using the Spearman Correlation method. The main purpose of the study is to determine the suitable butter machine for a peanut paste production factory. Contribution of this study to the literature PSI, SV and MARCOS methods were used together for the first time. In addition, no study has been found in the literature related to peanut butter machine. Therefore, this study is original and contributes to the literature.","PeriodicalId":44076,"journal":{"name":"International Journal of Knowledge-Based and Intelligent Engineering Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89648699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Solving barrier ranking in clean energy adoption: An MCDM approach with q-rung orthopair fuzzy preferences 清洁能源采用障碍排序问题的求解:一种具有q阶矫形模糊偏好的MCDM方法

IF 0.7

International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2023-07-13 DOI: 10.3233/kes-230048

R. Krishankumar, D. Pamučar

{"title":"Solving barrier ranking in clean energy adoption: An MCDM approach with q-rung orthopair fuzzy preferences","authors":"R. Krishankumar, D. Pamučar","doi":"10.3233/kes-230048","DOIUrl":"https://doi.org/10.3233/kes-230048","url":null,"abstract":"With a growing focus from the United Nations to eradicate the ill effects of climate change, countries around the world are transforming to green and sustainable habits/practices. Adoption of clean energy for demand satisfaction is a prime focus of many countries as it reduces carbon trace and promotes global development. In developing countries like India, there is an urge for sustainable global development. Literature shows that direct and complete adoption of clean energy incurs some barriers, which impede the sustainable development of the nation. Grading such barriers supports policymakers to effectively plan strategies, which motivates authors to put forward a novel decision model with integrated approaches. First, qualitative rating data on barriers and circular economy (CE) factors are collected from experts via questionnaires, which are transformed into q-rung orthopair fuzzy information (qRFI). Second, the weights of experts and CE factors are determined by the proposed variance measure and CRITIC. Third, barriers are graded by the proposed ranking algorithm that considers modified WAPAS formulation. Finally, these approaches are integrated into a model that is testified for practicality by using a case example from India. Sensitivity and comparative analyses are performed to realize the merits and limitations of the model for extant works.","PeriodicalId":44076,"journal":{"name":"International Journal of Knowledge-Based and Intelligent Engineering Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80707866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Dimensionality reduction technique under picture fuzzy environment and its application in decision making 图像模糊环境下的降维技术及其在决策中的应用

IF 0.7

International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2023-07-13 DOI: 10.3233/kes-230031

Preeti Devi, Bartłomiej Kizielewicz, A. Guleria, A. Shekhovtsov, N. Gandotra, Namita Saini, W. Sałabun

{"title":"Dimensionality reduction technique under picture fuzzy environment and its application in decision making","authors":"Preeti Devi, Bartłomiej Kizielewicz, A. Guleria, A. Shekhovtsov, N. Gandotra, Namita Saini, W. Sałabun","doi":"10.3233/kes-230031","DOIUrl":"https://doi.org/10.3233/kes-230031","url":null,"abstract":"The notion of soft matrix plays a vital role in many engineering applications and socio-economic and financial problems. A picture fuzzy set has been used to handle uncertainty data in modeling human opinion. In this work, we recall the picture fuzzy soft matrix concept and its different subsequent classes. Also, different kinds of binary operations over the proposed matrices have been provided. The main contribution of this paper is that using the concept of choice matrix and its weighted form and the score matrix, a new algorithm for decision-making has been outlined by considering the picture of fuzzy soft matrices. The current challenge In the decision-making problems is that many qualitative and quantitative criteria are involved. Hence, the dimensionality reduction technique plays an essential role in simplicity and broader applicability in the decision-making processes. We present an algorithm for the reduction process using the proposed definitions of the object and parameter-oriented picture fuzzy soft matrix and the technique to find the threshold value for the provided information. Then, illustrative numerical examples have also been provided for each proposed algorithm. A detailed comparative study of the proposed techniques has also been carried out in contrast with other existing techniques.","PeriodicalId":44076,"journal":{"name":"International Journal of Knowledge-Based and Intelligent Engineering Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90170997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Ontological knowledge inferring approach: Introducing Directed Collocations (DC) and Joined Directed Collocations (JDC) 本体知识推理方法:引入有向搭配(DC)和连接有向搭配(JDC)

IF 0.7

International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2023-06-09 DOI: 10.3233/kes-221516

Muditha Tissera, R. Weerasinghe

{"title":"Ontological knowledge inferring approach: Introducing Directed Collocations (DC) and Joined Directed Collocations (JDC)","authors":"Muditha Tissera, R. Weerasinghe","doi":"10.3233/kes-221516","DOIUrl":"https://doi.org/10.3233/kes-221516","url":null,"abstract":"The growing need of utilizing unstructured knowledge embedded in open-domain natural language text into machine-processable forms requires the induction of hardly extracted structured knowledge into knowledge bases which makes the Semantic Web vision a reality. In this context, ontologies, and ontological knowledge (triples) plays a vital role. This research introduces two novel concepts named Directed Collocation (DC) and Joined Directed Collocation (JDC) along with a methodical application of them to infer new ontological knowledge. Introduced Quality-Threshold-Value (QTV) parameter improves the quality of the inferred ontological knowledge. Having set a moderate value (3) for QTV, this approach inferred 95,491 new ontological knowledge from 43,100 triples of open domain Sri Lankan English news corpus. Indeed, the outcome was approximately doubled in size as the source corpus. Some inferred ontological knowledge was identical with the original corpus content, which evidences the accuracy of this approach. The remaining were validated using inter-rater agreement method (high reliability) and out of which around 56% were estimated as effective. The inferred outcome which is in the triple format may use in any knowledge base. The proposed approach is domain independent. Thus, helps to construct/extend ontologies for any domain with the help of less or no human specialists.","PeriodicalId":44076,"journal":{"name":"International Journal of Knowledge-Based and Intelligent Engineering Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86937291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CoBiCo: A model using multi-stage ConvNet with attention-based Bi-LSTM for efficient sentiment classification CoBiCo:一个使用多阶段卷积神经网络和基于注意力的Bi-LSTM进行高效情感分类的模型

IF 0.7

International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2023-05-29 DOI: 10.3233/kes-230901

R. Ranjan, A. Daniel

{"title":"CoBiCo: A model using multi-stage ConvNet with attention-based Bi-LSTM for efficient sentiment classification","authors":"R. Ranjan, A. Daniel","doi":"10.3233/kes-230901","DOIUrl":"https://doi.org/10.3233/kes-230901","url":null,"abstract":"The rapid growth of social media and specialized websites that provide critical product reviews has resulted in a massive collection of information for customers worldwide. These data could contain a wealth of information, such as product reviews, market forecasting, and the polarity of sentiments. In these challenges, machine learning and deep learning algorithms give the necessary capabilities for sentiment analysis. In today’s competitive markets, it’s critical to grasp reviewer opinions and sentiments by extracting and analyzing their characteristics. The research aims to develop an optimised model for evaluating sentiments and categorising them into proper categories. This research proposes a unique, novel hybridised model that integrates the advantages of deep learning methods Dual LSTM (Long Short Term Memory) and CNN (Convolution Neural Network) with word embedding technique. The performance of different word embedding techniques is compared to select the best embedding for the implementation in the proposed model. Furthermore, a multi-convolution approach with attention-oriented BiLSTM is applied. To test the validity of the performance of the proposed model, standard metrics were applied. The outcome indicates that the suggested model achieves a significantly improved accuracy of 96.56%, superior to other models.","PeriodicalId":44076,"journal":{"name":"International Journal of Knowledge-Based and Intelligent Engineering Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85500028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-agent based coalition formation of prosumers in microgrids using the i* goal modelling 基于i*目标模型的微电网产消者多智能体联盟形成

IF 0.7

International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2023-05-29 DOI: 10.3233/kes-230902

Sreenithya Sumesh, A. Krishna

{"title":"Multi-agent based coalition formation of prosumers in microgrids using the i* goal modelling","authors":"Sreenithya Sumesh, A. Krishna","doi":"10.3233/kes-230902","DOIUrl":"https://doi.org/10.3233/kes-230902","url":null,"abstract":"In this paper, we discuss the role of microgrids as a “prosumer”. Microgrids are used to provide locally generated power (energy), and this concept is becoming increasingly prominent with time. Microgrids have added economic value when assuming the role of “prosumer” or “group of prosumers”. A new outlook in managing prosumers connected to the energy sharing network has led to the creation of prosumer coalition groups, which can subsequently manage numerous goals in microgrid energy systems. For achieving prosumer energy goals, Goal-Oriented Requirements Engineering (GORE) is deployed in this work. Hence, the purpose of this research is to develop prosumer coalition-GORE artefacts, strategising GORE players, modelling non-functional requirements and ensuring sustainable requirements engineering management in the microgrid energy system. In this research, an i* goal model has been used to design a payoff function based on the game theory concept. The key to the pricing function is its fair distribution of payoffs depending on their surplus energy generation, thus providing optimum satisfaction to the buyer. With the objective of maximising the profits earned by prosumers through intra-microgrid energy trading, this paper also designs multi-objective functions to provide optimal value by using the i* goal model. By integrating Java with the IBM CPLEX optimisation tool, a simulation model based on the proposed method was developed and analysed. The results show that the proposed approach yields better outcomes when meeting the requirements of fairness and efficiency, reducing the intermittency effect of generation through renewable resources.","PeriodicalId":44076,"journal":{"name":"International Journal of Knowledge-Based and Intelligent Engineering Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88277969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Models for multiple attribute decision making with some interval-valued 2-tuple linguistic Pythagorean fuzzy Bonferroni mean operators 含区间值二元语言毕达哥拉斯模糊Bonferroni均值算子的多属性决策模型

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International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2020-02-10 DOI: 10.3233/kes-190417

Jie Wang, Mao Lu, G. Wei

引用次数: 0

CCEE: Clustering with chicken swarm based energy efficient algorithm with APUGR protocol for mobility awareness and energy saving in adhoc network CCEE:基于APUGR协议的基于鸡群的聚类节能算法在自组织网络中的移动感知和节能

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International Journal of Knowledge-Based and Intelligent Engineering Systems Pub Date : 2018-07-26 DOI: 10.3233/kes-180380

T. Santhi Sri, J. Rajendra Prasad, R. Kiran Kumar

引用次数: 1