Comfort Prediction of Office Chair Surface Material Based on the ISSA-LSSVM

This study serves the purpose of assisting users in selecting a comfortable seat surface material for office chairs and enhancing users' comfort while using office chairs. To address the issue that the selection of traditional seat surface material is too subjective and that the prediction effect is poor, an improved sparrow search algorithm (ISSA) optimized least squares support vector machine (LSSVM) method for office chair seat surface material comfort prediction has been proposed. Sparrow Search Algorithm (SSA) was optimized with Sobol sequences, nonlinear inertial weights, and a crisscross optimization algorithm to produce the Improved Sparrow Search Algorithm (ISSA), and then the relevant parameters of the LSSVM algorithm were optimized with the modified algorithm to improve its prediction performance. The prediction accuracy of the ISSA-LSSVM model is as high as 95.75% by combining the body pressure distribution experiments; the root mean square error (RMSE) is 0.29; the goodness of fit (R²) is 0.92; the mean absolute error (MAE) is 0.24; the standard deviation (RSD) is 5.99%. The ISSA-LSSVM model predicts seat surface material comfort more accurately and reliably. This strategy can assist consumers to narrow down their seat surface material choices and even suggest an optimal selection. In this way, it can boost users' pleasure with office chairs, which has great potential for wide application.

Review on Development of High-Static–Low-Dynamic-Stiffness Seat Cushion Mattress for Vibration Control of Seating Suspension System

This review focuses on studying passive vibration isolation techniques and their applications. Advantages and disadvantages of different vibration isolation techniques will be compared in order to find an innovative method to reduce seating suspension system vibration and improve the ride comfort of vehicles’ drivers. Quasi-zero stiffness (QZS) isolators of high-static–low-dynamic stiffness are found to have good application prospects in low-frequency vibration isolation. In order to improve the isolation performance of the seating suspension system, a specially made seat cushion will be studied where a quasi-zero stiffness (QZS) isolator such as a double-diamond isolator is selected as one of the cells/units/elements of the seat cushion mattress. The double-diamond isolator structure does not represent the whole seating suspension system. The transmissibility ratio of the double-diamond isolator is evaluated by analytical and simulation models and compared to that of a conventional linear spring isolator. Although the performance of the passive vibration isolation/control system is usually worse than that of the active or semi-active control system, the cost of the passive vibration isolation/control system is lower than that of the active and semi-active control system, and the relative simplicity of adding a vibration isolation cushion mattress in an existing passive seating suspension system makes it low in cost, easy to implement, and more attractive than the active and semi-active vibration control systems.

A Novel Multi-Attribute Decision Making Method Based on The Double Hierarchy Hesitant Fuzzy Linguistic Generalized Power Aggregation Operator

. A double hierarchy hesitant fuzzy linguistic term set (DHHFLT) is deemed as an effective and powerful linguistic expression which models complex linguistic decision information more accurately by using two different hierarchy linguistic term sets. The purpose of this paper is to propose a multi-attribute decision making method to tackle complex decision issues in which attribute values are represented as double hierarchy hesitant fuzzy linguistic numbers, and there are some extreme or unreasonable data in the attribute values. To do this, firstly, four double hierarchy hesitant fuzzy linguistic generalized power aggregation operators are introduced, including the double hierarchy hesitant fuzzy linguistic generalized power average (DHHFLGPA) operator, the double hierarchy hesitant fuzzy linguistic generalized power geometric (DHHFLGPG) operator, and their weighted forms. Thereafter, several favorable properties, as well as representative cases of the proposed operators, are investigated in detail. Moreover, by virtue of the proposed operators, a novel approach is developed for coping with multi-attribute decision making cases in the double hierarchy hesitant fuzzy linguistic context. Finally, an illustrated example is given to demonstrate the practical application of the presented approach, an availability verification is given to show its validity, and a comparative analysis is also conducted to highlight the advantages of the proposed approach.

Generalized Linguistic Ordered Weighted Hybrid Logarithm Averaging Operators and Applications to Group Decision Making

In this paper, we develop the generalized linguistic weighted logarithm averaging (GLWLA) operator and the generalized linguistic ordered weighted logarithm averaging (GLOWLA) operator in the group decision making under the linguistic surrounding. Then some properties of the families of the GLOWLA operator by different weighting vector are investigated. Furthermore, we present the generalized linguistic ordered weighted hybrid logarithm averaging (GLOWHLA) operator, which extends the GLOWLA operator. We also construct a nonlinear goal programming model to determine GLOWHLA weights from observational linguistic variable values under partial weight information. Finally, a numerical example is given to illustrate the new approach to evaluating university faculty for tenure and promotion, which indicates the feasibility and effectiveness of the new approach.

POWER GEOMETRIC OPERATORS FOR GROUP DECISION MAKING UNDER MULTIPLICATIVE LINGUISTIC PREFERENCE RELATIONS

The aim of this paper is to develop some new linguistic aggregation operators, such as linguistic power geometric (LPG) operator, linguistic weighted PG operator, LPOWG operator which are based on PG operator. We have studied some desired properties of the developed operators, such as commutativity, idempotency, boundary, etc. Moreover, we have developed two approaches to deal with group decision making problems under multiplicative linguistic preference relations. If the weighting vector of the decision makers is known, we develop an approach which is based on the linguistic weighted PG operator. On the other hand, if the weighting vector of the decision makers is unknown, we develop another approach which is based on the LPOWG. Finally, a practical example is given to illustrate the multiple attribute group decision making process; a comparative study to the linguistic weighted geometric average (LWGA) operator method is also demonstrated.

A Satisfactory-Oriented Approach to Multiexpert Decision-Making With Linguistic Assessments

This paper proposes a multiexpert decision-making (MEDM) method with linguistic assessments, making use of the notion of random preferences and a so-called satisfactory principle. It is well known that decision-making problems that manage preferences from different experts follow a common resolution scheme composed of two phases: an aggregation phase that combines the individual preferences to obtain a collective preference value for each alternative; and an exploitation phase that orders the collective preferences according to a given criterion, to select the best alternative/s. For our method, instead of using an aggregation operator to obtain a collective preference value, a random preference is defined for each alternative in the aggregation phase. Then, based on a satisfactory principle defined in this paper, that says that it is perfectly satisfactory to select an alternative as the best if its performance is as at least "good" as all the others under the same evaluation scheme, we propose a linguistic choice function to establish a rank ordering among the alternatives. Moreover, we also discuss how this linguistic decision rule can be applied to the MEDM problem in multigranular linguistic contexts. Two application examples taken from the literature are used to illuminate the proposed techniques.