为了给人机界面设计提供有效的评价手段,围绕用户对人机界面的感性需求,提出了基于感性工学的人机界面多意象评价方法。首先运用感性工学方法建立感性指标评价体系,在指标权重分配上,通过将灰色关联分析法引入群层次分析(analytic hiera...为了给人机界面设计提供有效的评价手段,围绕用户对人机界面的感性需求,提出了基于感性工学的人机界面多意象评价方法。首先运用感性工学方法建立感性指标评价体系,在指标权重分配上,通过将灰色关联分析法引入群层次分析(analytic hierarchy process,AHP)法中,利用改进的群AHP法求取综合权重,解决了传统AHP法主观性过强的缺点;同时根据感性工学评价的模糊性,建立了一种直觉模糊集理论和TOPSIS(technique for order preference by similarity to an ideal solution)法相结合的综合评价模型。结合数控机床人机界面设计方案验证了该评价方法的有效性和可行性。该方法对人机界面感性设计与设计评价具有一定的参考意义。展开更多
An improved technique for order preference by similarity to ideal solution （TOPSIS） algorithm, SAE-TOPSIS, is proposed for the vertical handoff decision in heterogeneous wireless networks. The signal to interference...An improved technique for order preference by similarity to ideal solution （TOPSIS） algorithm, SAE-TOPSIS, is proposed for the vertical handoff decision in heterogeneous wireless networks. The signal to interference plus noise ratio （SINR） effects, analytic hierarchy process （AHP） and infor- mation entropy （SAE） weight method were introduced into the algorithm. Handoff decision meeting the multi-attribute quality of service （QoS） requirement is made according to an attribute matrix and weight vector using the TOPSIS algorithm. The simulation results have shown that the proposed algo- rithm can provide satisfactory performance fitted to the characteristics of the traffic.展开更多
文摘为了给人机界面设计提供有效的评价手段,围绕用户对人机界面的感性需求,提出了基于感性工学的人机界面多意象评价方法。首先运用感性工学方法建立感性指标评价体系,在指标权重分配上,通过将灰色关联分析法引入群层次分析(analytic hierarchy process,AHP)法中,利用改进的群AHP法求取综合权重,解决了传统AHP法主观性过强的缺点;同时根据感性工学评价的模糊性,建立了一种直觉模糊集理论和TOPSIS(technique for order preference by similarity to an ideal solution)法相结合的综合评价模型。结合数控机床人机界面设计方案验证了该评价方法的有效性和可行性。该方法对人机界面感性设计与设计评价具有一定的参考意义。
基金Supported by the National Natural Science Foundation of China （No. 60872018）, the Natural Science Foundation of Education Committee of Jiangsu Province （ No. 11KJB510014） and Scientific Research Foundation of NUPT （ No. NY210004）.
文摘An improved technique for order preference by similarity to ideal solution （TOPSIS） algorithm, SAE-TOPSIS, is proposed for the vertical handoff decision in heterogeneous wireless networks. The signal to interference plus noise ratio （SINR） effects, analytic hierarchy process （AHP） and infor- mation entropy （SAE） weight method were introduced into the algorithm. Handoff decision meeting the multi-attribute quality of service （QoS） requirement is made according to an attribute matrix and weight vector using the TOPSIS algorithm. The simulation results have shown that the proposed algo- rithm can provide satisfactory performance fitted to the characteristics of the traffic.
