With the concept of sustainable development, enterprises are facing severe challenges in ecological protection and economic development. Approaches to improving effectiveness of the coordinated development strategy must continue to evolve to address uncertainty and hazards that may be encountered in the future. We propose a coordinated development strategy model based on the combination of soft fuzzy and rough set theory and construct its prediction model. For the multistrategy dataset in the paper, parameter for each kind shall be selected through converting the multistrategy data into two prediction datasets. An algorithm transformed by SFRC shall be subject to weighted average for each parameter. Furthermore, we use training methods and soft fuzzy rough sets’ learning algorithm to calculate, and the evaluating indicator rough set is constructed with a three-tier model structure. After the final rough set training is completed, test results show that the rough set model which has a higher rating accuracy builds a better completed business performance evaluation. By comparing the prediction effect, both SVM algorithm and multistrategy prediction model for the soft fuzzy rough set in the paper can realize effective prediction for the enterprise’s coordinated development strategy. Moreover, the prediction result obtained at the time of adopting boundary to get the expected value is superior to that of giving one fixed threshold. It shows that the prediction performance of the algorithm in the paper is more excellent and represents the advantage of the algorithm prediction performance at the time of adopting boundary to get the expected value. The model provides support methods to assist enterprise management in making more efficient and scientific decisions for enterprise’s coordinated development.

中文翻译：

---

用软模糊粗糙集建模企业协调发展战略

秉持可持续发展理念，企业在生态保护和经济发展方面面临严峻挑战。必须不断改进提高协调发展战略有效性的方法，以应对未来可能遇到的不确定性和危害。提出了一种基于软模糊和粗糙集理论相结合的协调发展战略模型，并构建了其预测模型。对于本文中的多策略数据集，通过将多策略数据转换为两个预测数据集来选择每种参数。SFRC 转换的算法对每个参数进行加权平均。此外，我们使用训练方法和软模糊粗糙集的学习算法来计算，评价指标粗糙集采用三层模型结构构建。在最终的粗糙集训练完成后，测试结果表明，具有更高评级准确率的粗糙集模型构建了更好的完成业务绩效评估。通过比较预测效果，本文提出的软模糊粗糙集的SVM算法和多策略预测模型都可以实现对企业协调发展战略的有效预测。而且，采用边界得到期望值时得到的预测结果优于给出一个固定阈值的预测结果。说明文中算法的预测性能更加优异，代表了算法在采用边界获取期望值时预测性能的优势。该模型为辅助企业管理层为企业协调发展做出更高效、更科学的决策提供了支持方法。