Weight Calculation Research Articles

Soft sensing modeling of penicillin fermentation process based on local selection ensemble learning

In the process of penicillin fermentation, there is a strong nonlinear relationship between the input eigenvector and multiple output vectors, which makes the prediction accuracy of the existing model difficult to meet the requirements of chemical production. Therefore, a local selective ensemble learning multi-objective soft sensing modeling strategy is proposed in this study. Firstly, a localization method based on transfer entropy and k-means is proposed to reconstruct the sample set. Then, based on the reconstructed local samples, the local soft sensing model is established by the multi-objective support vector regression method, and the selective ensemble of sub-models and the adaptive calculation of prediction weights are realized. At the same time, to reduce the adverse effects caused by improper selection of model parameters, the sparrow search algorithm is used to realize the tuning of the mentioned model parameters. Finally, the proposed modeling strategy is simulated. The results show that, compared with other methods, the proposed local selective ensemble learning multi-objective soft sensing modeling strategy has better prediction performance.

Carbon Emission Prediction Algorithm for Community Electricity Consumption Based on Improved PSO Algorithm with Optimized Autoregressive Moving Average Models

Abstract The anticipation of carbon emissions stemming from community electricity usage stands as a pivotal field of study. Such analysis holds the potential to furnish communities with informed pathways towards crafting viable carbon reduction strategies, thereby contributing significantly to the overarching goals of carbon peaking and eventual neutrality. The intricacies of carbon emissions from community electricity consumption are manifold, entangled with variables like energy consumption patterns, energy mix, and carbon emission coefficients. Hence, the imperative lies in crafting a predictive framework adept at holistically integrating these variables to enhance prognostic precision and reliability. Within this research, we propose a dynamic carbon emission factor regression model. This model is uniquely poised to capture real-time shifts influenced by changes in energy structure and policy landscapes, thereby amplifying predictive sensitivity. Leveraging the Particle Swarm Optimization (PSO) algorithm, we synchronously optimize the autoregressive terms (p) of the Autoregressive Integrated Moving Average (ARIMA) model and the moving average terms (q) of the MA model to attain a globally optimal solution. Crucially, this approach obviates the need for manual intervention and arbitrary parameter selection. In contrast to conventional optimization methodologies, our paper advances the PSO’s weight calculation mechanism. By assigning greater weight values during the initial iterations, the algorithm maintains robust global search capabilities. Subsequently, the inertia weight diminishes progressively throughout the iteration process, fostering precise local exploration.

A deep learning model for estimating body weight of live pacific white shrimp in a clay pond shrimp aquaculture

This paper presents a novel approach to address the essential challenge of accurately determining the total weight of shrimp within aquaculture ponds. Precise weight estimation is crucial in mitigating issues of overfeeding and underfeeding, thus enhancing efficiency and productivity in shrimp farming. The proposed system leverages image processing techniques to detect individual live shrimp and extract pertinent features for weight estimation within a clay pond environment. Specifically, an automated feed tray captures images of live shrimp, which are then processed using a combination of Detectron2, PyTorch, and CUDA (Compute Unified Device Architecture) for individual shrimp detection. Essential features such as area, perimeter, width, length, and posture are extracted through image analysis, enabling accurate estimation of shrimp weight. An Artificial Neural Network (ANN) model, utilizing these features, accurately predicts shrimp weight with a coefficient of determination (R2) of 94.50% when incorporating all extracted features. Furthermore, our system integrates a user-friendly web application that empowers farmers to monitor shrimp weight trends, facilitating precision feeding strategies and effective farm management. This study contributes a low-cost solution using a deep learning model to estimate the weight of live Pacific white shrimp in clay ponds, enabling daily weight calculations, helping farmers optimize feed quantities, providing shrimp size distribution insights, and reducing the Feed Conversion Ratio (FCR) for greater profitability. The procedure for shrimp feature extraction is also provided, including the calculation of shrimp length and width, as well as shrimp posture classification.

Establishing a user demand hierarchy model driven by a mental model for complex operating systems

In complex human-computer interactions, issues such as task failures, system malfunctions, and frequent accidents caused by user errors are common. Therefore, it is necessary to study complex system interactions to enhance overall efficiency. This study focuses on the task interface of a digital twin system for computer numerical control (CNC) machine tools and examines the relationship between the user mental model and interface design elements. Key mental information is obtained through questionnaires and interviews, forming the basis for establishing a user mental model. High-frequency information words are extracted, experimental samples are designed, and importance rating surveys are conducted. Quantitative analysis methods, including factor analysis and weight calculation, are utilized to analyze the needs of target users. Consequently, a user demand hierarchy model is constructed. This approach aims to effectively reduce user errors in the human-computer interaction process within complex systems and enhance cognitive efficiency.

Comprehensive vulnerability assessment for environmental facility depending on spatial characteristics in South Korea

Among environmental facilities, wastewater treatment facilities have a crucial role in sustaining human life, and any occurrence of an earthquake or flood within these facilities can result in various social, economic, and environmental issues, either directly or indirectly. Therefore, a quantitative vulnerability assessment of wastewater treatment facilities is necessary to minimize and prevent damage from earthquakes and flood disasters. For this reason, this study introduces a novel indicator to assess the susceptibility of disasters, considering aspects of exposure, sensitivity, and adaptive capacity. The newly proposed indicator encompasses numerous evaluation criteria, topography, natural surroundings, hydraulic systems, structural composition, and non-structural features. Also, Weights derived using the combined weight calculation (CWC) method, which combined the analytic hierarchy process (AHP) and entropy weight method were applied to the indicator. It was tested across 23 cities to validate its efficacy, revealing a substantial correlation between the vulnerability index and the specific attributes of the city's wastewater treatment facilities. Therefore, this study analyzed wastewater treatment facilities by comparing the attributes of the urban areas under investigation, such as topological characteristics, urbanization levels, population density, infrastructure quality, and disaster preparedness resources available. The suggested methodology can facilitate the development of strategies aimed at averting damage caused by earthquakes or floods and reducing the adverse impact on wastewater treatment facilities while considering the unique characteristics of the urban setting in question.

Integrated Evaluation Method of Bus Lane Traffic Benefit Based on Multi-Source Data

Bus lanes are an important measure for improving the quality of bus service and the efficiency of transportation systems. A scientific and reasonable evaluation of the overall traffic operation efficiency of the bus priority road section is helpful to fully understand the improvement effect of the introduction of bus lanes on traffic operation. To comprehensively and objectively evaluate the traffic benefits of bus lanes, the Delphi and grey correlation methods were used to construct a comprehensive weight calculation model of the indicators. The weights of eight traffic benefit evaluation indicators at the two levels of buses and general traffic were calculated, and the weights were then optimized using the target optimization model. Combined with different weight indexes, the evaluation of the traffic benefit level of the bus lane was realized using the matter-element extension model based on the improvement in the sticking progress. The bus lanes of the Daping-Yangjiaping, Huanghuayuan interchange-Luneng turntable, and Dashiba-Hongqihegou routes in the main urban area of Chongqing were used for verification. The results show that the traffic benefits of the three case areas have been improved to a certain extent after the construction of bus lanes, but the benefit level has not changed. Through the analysis of various operating indicators, the weaknesses that affect the traffic efficiency can be obtained, and then the decision-making basis for the implementation and improvement of the bus lane optimization scheme can be provided.

Personalized movie recommendations based on probabilistic linguistic sentiment and integrated DEMATEL-TODIM methods

With the development of society, online reviews are increasingly becoming a crucial factor in decision-making. Especially for entertainment products such as movies, they are preferred for their affordability and high entertainment factor. Therefore, this paper proposes a movie recommendation model that considers user personalization using a probabilistic linguistic approach based on online reviews. Firstly, the method constructs a quantitative sentiment framework that transforms comments into a multi-granular probabilistic sentiment language. Secondly, we build the decision-making trial and evaluation laboratory (DEMATEL) method for probabilistic linguistic environments to explore interrelationships between product attributes, and improve the distance measure and score function to better integrate probabilistic linguistic information into DEMATEL weight calculations. Furthermore, to account for risk preferences, the model employs the extended TODIM (an acronym in Portuguese for interactive and multicriteria decision making) methodology to determine the ranking of alternatives. Finally, we design Douban movie ranking experiments to demonstrate the validity of the model. Compared with other methods, this paper incorporates the emotional tendency of movie attributes and user preference into the decision-making process leading to more reasonable results.

Geometric interpretation of efficient weight vectors

Pairwise comparison matrices (PCMs) are frequently used in different multicriteria decision making problems. A weight vector is said to be efficient if no other weight vector is at least as good in estimating the elements of the PCM, and strictly better in at least one position. Understanding the efficient weight vectors is crucial to determine the appropriate weight calculation technique for a given problem. In this paper we study the set of efficient weight vectors for three and four dimensions (alternatives) from a geometric viewpoint, which is a complementary to the algebraic approach used in the literature. Besides providing well-interpretable demonstrations, we also draw attention to the particular role of weight vectors calculated from spanning trees. Weight vectors corresponding to line graphs are vertices of the (polyhedral, but usually nonconvex) set of efficient weight vectors, while weight vectors corresponding to other spanning trees are also on the boundary.

Dachengqi decoction dispensing granule ameliorates LPS-induced acute lung injury by inhibiting PANoptosis in vivo and in vitro

Ethnopharmacological relevanceAcute lung injury (ALI) is a serious health-threatening syndrome of intense inflammatory response in the lungs, with progression leading to acute respiratory distress syndrome (ARDS). Dachengqi decoction dispensing granule (DDG) has a pulmonary protective role, but its potential modulatory mechanism to alleviate ALI needs further excavation. Aim of the studyThis study aims to investigate the effect and potential mechanism of DDG on lipopolysaccharide (LPS)-induced ALI models in vivo and in vitro. Materials and methodsLPS-treated Balb/c mice and BEAS-2B cells were used to construct in vivo and in vitro ALI models, respectively. Hematoxylin-eosin (HE), Wet weight/Dry weight (W/D) calculation of lung tissue, and total protein and Lactic dehydrogenase (LDH) assays in BALF were performed to assess the extent of lung tissue injury and pulmonary edema. Enzyme-linked immunosorbent assay (ELISA) was used to detect the levels of tumor necrosis factor-alpha (TNF-α), interleukin-1β (IL-1β), and interleukin-18 (IL-18) in BALF, serum, and cell supernatant. The qRT-PCR was used to detect inflammatory factors, Z-DNA binding protein 1 (ZBP1), and receptor-interacting protein kinase 1 (RIPK1) expression in lung tissues and BEAS-2B cells. Double immunofluorescence staining and co-immunoprecipitation were used to detect the relative expression and co-localization of ZBP1 and RIPK1. The effects of LPS and DDG on BEAS-2B cell activity were detected by Cell Counting Kit-8 (CCK-8). Western blot (WB) was performed to analyze the expression of PANoptosis-related proteins in lung tissues and BEAS-2B cells. ResultsIn vivo, DDG pretreatment could dose-dependently improve the pathological changes of lung tissue in ALI mice, and reduce the W/D ratio of lung, total protein concentration, and LDH content in BALF. In vitro, DDG reversed the inhibitory effect of LPS on BEAS-2B cell viability. Meanwhile, DDG significantly reduced the levels of inflammatory factors in vitro and in vivo. In addition, DDG could inhibit the expression levels of PANoptosis-related proteins, especially the upstream key regulatory molecules ZBP1 and RIPK1. ConclusionDDG could inhibit excessive inflammation and PANoptosis to alleviate LPS-induced ALI, thus possessing good anti-inflammatory and lung-protective effects. This study establishes a theoretical basis for the further development of DDG and provides a new prospect for ALI treatment by targeting PANoptosis.

Application of the new simple weight calculation (SIWEC) method in the case study in the sales channels of agricultural products

In this research is presented a new method for determining the weights of criteria called simple weight calculation (SIWEC) method. The steps of this method are presented in the practical example of determining the importance of criteria for the needs of sales of agricultural products in the Semberija region. During the presentation of this method two methods are elaborated the simple SIWEC method which includes numerical ratings and the fuzzy SIWEC method which includes ratings in the form of linguistic value. In the selected example is presented how to use this method in order to determine the importance of criteria and in both cases the criterion of sales reliability is given the greatest weight. The contribution SIWEC method is reflected in its simplicity, which facilitates decision-making.•The method presented in this research apart from others is that it uses the evaluation of the criteria by decision makers, so the criteria should not be ranked and compared, but simply evaluated.•Unlike similar methods, the presented method uses the adjusted steps of the method for ranking the alternatives, and decision makers are given a different importance in the decision-making.

Compatible multi-model output fusion for complex systems modeling via set operation-based focus data identification

Is an inferior model completely useless in complex systems modeling? This study proposes a novel multi-model output fusion approach that makes the best of the outputs from multi-models, i.e., using the limited superior results from inferior models to compensate for certain inferior results from even superior models. For fusing the outputs from multi-models, the weight assigned to each output is calculated based on two factors, namely the accuracy of each model and the similarity between the testing input and the focus data used for constructing the respective model. Specifically for similarity calculation, the focus data list is identified based on set operations. There are three theoretical contributions of this study, namely accuracy-and-similarity-based weight calculation, the set-operation-based similarity calculation which is an addition to traditional distance-based calculation, and the high compatibility of the proposed approach which is independent from any baseline approach. A practical case of overall reconnaissance capability evaluation of the Unmanned Aerial Vehicle (UAV) swarm is studied for validation. Primary results indicate that the proposed approach can outperform two single models: the backpropagation neural network (BPNN) and the Radial Basis Function (RBF) neural network. Further validations demonstrate that the proposed approach also outperforms multi-model output fusion with equal weights, without model accuracy, with varied focus data percentages ranging from 0.1 to 0.9. More importantly, the proposed approach remains effective in four different conditions of multi-model outputs fusion with improvements from 9.58 % to 38.03 %.

Weight assignment in cloud service selection based on FAHP and rough sets

Cloud computing is becoming the most widely used technology as the next-generation platform for conducting business. Many cloud providers offer the same functionalities, but have different quality of service (QoS) attributes. Thus the selection of cloud services, which meets the user-desired QoS requirements, has become increasingly complex. In this paper, we present a method that integrates both subjective and objective weights for evaluating the cloud services. This method is based on rough set theory and a proposed extended version of Fuzzy Analytic Hierarchy Process (FAHP) and takes into consideration the trust level associated with the experts, whose evaluations are considered in the calculation of subjective weights, and the preferences of the end user.

Assessing the Impact of Criterion Weights on the Ranking of the Top Ten Universities in Vietnam

This study focuses on evaluating the influence of criterion weights on the ranking of the top ten universities in Vietnam. Criteria weights were determined using four different methods, including the equal weight method, the weights of the Vietnam University Rankings (VNUR) system, the entropy weight method, and the Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) weight method. Four university ranking methods were applied: Proximity Indexed Value (PIV), Ranking of Alternatives with Weights of Criterion (RAWEC), Root Assessment Method (RAM), and Simple Ranking Process (SRP). The results indicate that the use of different weight calculation methods does not significantly affect university rankings. The four leading universities in Vietnam consistently maintain their position in the rankings, regardless of the weight calculation or ranking methods used.

Study on stability evaluation of goaf based on AHP and EWM—taking the northern new district of Liaoyuan city as an example

Throughout the history of coal mining in all countries of the world, large areas of goaf have been left behind, and sudden collapses and surface subsidence of large areas of goaf may occur, especially for mining areas with long mining cycles. The northern new district of the Liaoyuan mining area has been subjected to nearly half a century of mining activities, accompanied by a gradual accumulation of disasters, which have occurred frequently in recent years. In order to assess the stability of the goaf in the study area, this paper proposes a hybrid decision-making multi-factor integrated evaluation method. The distribution of underground goafs was determined using geophysical exploration techniques (seismic survey and transient electromagnetic method) and geological drilling exploration. First, an evaluation index system was established based on the specifications of the goaf, the ecological and geological environment, and the mining conditions; the system included 14 indicators. Two weight calculation methods, AHP-EWM, were employed to determine the comprehensive weight of each indicator by combining subjective and objective weights on the basis of improved game theory. Subsequently, the fuzzy comprehensive evaluation method was utilised to complete the stability rating of each block in the study area, and MapGIS and ArcGIS were employed to complete the drawing of the stability zoning map of the northern new district goaf. The study area was divided into three zones of stability, basic stability and instability, according to the critical value. These zones accounted for 23.03%, 36.45% and 40.52% of the total area of the study area, respectively. The comprehensive on-site investigation revealed a decrease in the size and number of collapse pits and the rate of damage to the houses from the unstable zone to the stable zone. This indicates that the results of the division are consistent with the actual situation. The classification results are consistent with the actual ground disaster situation, thus verifying the rationality and validity of the evaluation method. The results indicate that the stability of the study area is generally at the lower middle level.

Evaluation of Determining the Best Product Promotion Media Decisions for MSMEs with ROC Ranking Technique and SAW Ranking Method

Micro, Small, and Medium Enterprises (MSMEs) face challenges in determining effective promotional media to increase sales of their products. This research aims to evaluate and determine the best promotional media for MSMEs using the ROC (Rank Order Centroid) ranking technique and the SAW (Simple Additive Weighting) method. The criteria used include Advertising Costs, Target Market, Promotion Time, and Brand Image. Based on the calculation of criteria weights with the ROC technique and evaluation of alternatives with the SAW method, Social Media was found to be the best promotional media, followed by Search Engines and Product Collaboration. Social Media has advantages in low cost, wide target market reach, and promotional flexibility and effectiveness. Search Engines and Product Collaboration also showed good results in reaching the target market and promotional flexibility. In contrast, Print Media ranked the lowest due to limited reach and high costs. This research provides guidance for MSMEs in choosing the right promotional media and optimizing resources for maximum promotional results.

Decision Support System for Determining the Best School Extracurricular Activities by Combining the ROC and MAUT Methods

The various extracurricular activities at school make students confused and difficult to choose which extracurricular activities are more suitable for participation. However, sometimes there are also students choosing extracurricular activities based on many of their friends. Therefore, determining the best school extracurricular activities is the best solution for students as a reference to find which is the best extracurricular activity. The criteria used in this study in choosing the best extracurricular activities are Regional Event Activities, Allocation, Creativity and Talent Channeling. By utilizing SPK, decision makers can make more systematic decisions, based on a deeper understanding of the various alternatives available and relevant criteria. SPK or decision support system is a technique that has the ability to determine a decision using a technical design based on alternatives and predetermined criteria. SPK or decision support system is a technique that has the ability to determine a decision using a technical design based on alternatives and predetermined criteria. In the context of extracurricular school selection, combining the ROC (Rank Order Centroid) and MAUT (Multi-Attribute Utility Theory) methods in a Decision Support System is an interesting approach. The ROC method is used to cluster and rank schools based on certain criteria, while MAUT helps in the calculation of appropriate weights for these criteria. By integrating these two methods, the SPK can provide a more structured guideline in the selection of extracurricular activities that suit students' interests and needs. The research results obtained show that the Futsal alternative is the first recommendation as the best extracurricular with a final value of 0.655086.

Downstream strategies of liquid smoke products as a preservative and smoke aroma in fishery products

Smoked fish is a fishery product that meets the nutritional needs of the population. The traditional smoking method leads to the production of H2S, which reduces the aroma and is carcinogenic. The liquid smoke technology offers a solution to the challenges associated with the application of traditional smoking methods. However, the use of the liquid smoke method remains limited in smoked fish businesses. This study aimed to evaluate and develop a downstream strategy for producing and distributing liquid smoke to facilitate its implementation by smoked fish businesses based on SWOT analysis. This study employed a quantitative descriptive methodology utilizing the strengths, weaknesses, opportunities, and threats (SWOT) analytical framework. The data were collected through interviews and questionnaires. The obtained data were subjected to weight calculations using the Expert Choice tool. The research findings indicate that the optimal approach for developing downstream liquid smoke products is to create a novel product in the form of liquid smoked fish. Liquid-smoked fish are immersed in or coated with liquid smoke to achieve an extended shelf life and smoky aroma, without traditional smoking methods. In addition, it establishes a strategic alliance between scholars, entrepreneurs, and the government. Strategic relationships can be established by developing a shared agenda focusing on fostering a sustainable blue economy. The blue economy refers to the use of hygienic, healthy, and non-carcinogenic fishing products such as smoked fish to promote sustainable economic growth and enhance community welfare.

Hubungan Indeks Massa Tubuh Terhadap Kelincahan Pemain Futsal Academy Al-Hadid Surabaya Usia 20 Tahun

The dominant characteristics of movement in futsal are fast and agile in changing direction of movement, which is explained as agility. To maximize the physical components of agility, an ideal body composition will certainly be needed, which can be seen through the body mass index. Body mass index is a measuring tool to determine a person's ideal body composition through the calculation of weight and height. This study investigates the relationship between body mass index and agility of futsal players at the AL-Hadid Academy Surabaya aged 20 years in 2024. This study uses a quantitative descriptive approach that focuses on correlation. The data collection method is carried out using 2 instruments, including measuring height and weight to calculate body mass index with the formula and conducting an agility test using the illinois agility test which is only measured once on each instrument. Body mass index is the independent variable in this study, and agility is the dependent variable. using descriptive statistical data analysis methods, linearity tests, and product moment correlation analysis. The results of data analysis show that body mass index has a linear relationship in the linearity test with a significant deviation form linearity value of 0.165> 0.05. Then in the product moment correlation test, a significance value of 0.000 and a correlation coefficient value of 0.709 were obtained, which can be said to be correlated, the direction of the relationship is positive, and indicates a very strong degree of relationship. Based on the statistical results, it can be concluded that body mass index has a very strong relationship to the agility of futsal players.

Research on Identification of the Capacity Influencing Factors of Youth Sports Clubs in China

Since the 1970s, nonprofit organizations have identified organizational capacity as the key to improving organizational effectiveness. Youth sports clubs have long been trapped in a predicament that makes it difficult for them to keep non-profit nature, operate independently and maintain high performance for a long time. This study investigates which influencing factors can act on the capacity of youth sports clubs to ensure their non-profit nature whilst achieving healthy and sustainable development. The organizational theory systems view emphasizes the relationship between open internal structures and the role of external environmental factors, therefore the capacity influencing factors of youth sports clubs can be comprehensively considered to achieve this by considering both the internal and external influencing components of organizational capacity. The focus of this study was obtained by searching 11 relevant policy documents, 21 papers, and in-depth interviews with 26 experts including youth sports club managers, coaches, and venue management personnel and scholars studying in the field of youth sports research or practice. The study revealed the internal and external influences on youth sports club capabilities, including strategic leadership, service innovation, resource acquisition, network relationships, policy, social media, and environmental uncertainty; and constructed a relationship between internal and external influences on youth sports club capabilities and organizational effectiveness. In addition, we found that Social media had the highest weight, policy had the lowest weight, and the rest of the influences did not differ significantly by the method of the weight calculation. We recommend that youth sports clubs increase the application of social media, stimulate employees' service and innovation ability, and cultivate the strategic leadership ability of leaders.

Wooden furniture design based on physiological-psychological measurement technology and Kansei engineering: Taking Ming-style chair as an example

Psychological and physiological cognitive measurements were combined with Kansei engineering theory to study the shape of the traditional Chinese official-hat chair, a kind of Ming-style chairs, while investigating people’s perceptual cognitive process. This work employed focus groups to obtain 5 groups of representative words and 22 typical samples for evaluation experiments. After data preprocessing, principal component analysis (PCA) was used to extract three main components: “Concise-Ornate”, “Soft-Strong”, and “Elegant-Vulgar”. In terms of component weight calculation, the analytic hierarchy process (AHP) was initially used to calculate the subjective cognitive weight of different components, and then eye-tracking technology was used to assist in calculating the physiological cognitive weight. Finally, combining the subjective and objective weights, the weights of the components were determined as: backrest (41.02%) > stretcher (18.29%) > handrail (11.64%) > top rail (11.14%) > outside stick (8.64%) > inside stick (5.32%) > foot rail (3.95%). The four main components—backrest, stretcher, handrail, and top rail—along with perceptual image evaluations, were selected to establish a multivariate linear regression equation, thereby constructing a mathematical mapping relationship between perceptual image and main design elements. This provides theoretical support for designers in creating different perceptual images.